{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority DIfferentials.MANUSCRIPT & DESCRIPTIVE RESULTS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 7 Aug 2024, 15:12:13
{txt}
{com}. 
.   
.    
. 
.   
. 
. **** 2nd ITERATION OF "STATUS GROUP DIFFERENTIALS AS REFERENCE POINTS FOR FOSTERING DIVERSITY AND INCLUSION WITHIN THE U.S. FEDERAL CIVILIAN WORKFORCE" [KRAUSE & PARK, NOVEMBER 2023] ****
. 
. 
. 
. 
. 
. 
. *** ACCESS DATABASE FOR THE PROJECT: FEVS DATA FROM 2010-2019 AND 'MATCHED' OPM DATA ****
. 
. 
. use "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\2010-2019_DATA FINAL.11-19-2023.dta", replace 
{txt}
{com}. 
.    
.    
. **************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
.  
.  
. 
. **** 0. COMPUTE OVERALL IN-GROUP/OUT-GROUP AGENCY EMPLOYMENT RATIO VARIABLES & LN TRANSFORMED VARIABLES *****
. 
. 
. gen ratio_fem_tot_men_tot = female_count / male_count
{txt}
{com}. *
. gen ratio_min_tot_nmin_tot = minority_count / nonminority_count
{txt}
{com}. 
. 
. 
. ** Add a "2.11" positive constant to ensure negative values of "diversity2" can be log computed [diversity2_min = -2.102011] 
. 
. gen lndiversity2zeroadj = ln(diversity2 + 2.11)
{txt}
{com}. *
. *
. *** NOTE FOR APPENDIX E: ORGANIZATIONAL JUSTICE LATENT DEPENDENT VARIABLE ***
. 
. ** Add a "2.47" positive constant to ensure negative values of "justice2" can be log computed [justice2_min = -2.46851] 
. 
. gen lnjustice2zeroadj = ln(justice2 + 2.47)
{txt}
{com}. 
. 
. 
. 
. * BETWEEN-IDENTITY GROUP DIFFERENTIAL: AGGREGATE [ALL AGENCY EMPLOYEES] PASSIVE REPRESENTATION COVARIATES: [WOMEN SUPERVISORS / MEN SUPERVIORS] &  [MINORITY SUPERVISORS / NON-MINORITY SUPERVISORS]
. gen ln_ratio_fem_tot_men_tot  = ln(ratio_fem_tot_men_tot)
{txt}
{com}. *
. gen ln_ratio_min_tot_nmin_tot = ln(ratio_min_tot_nmin_tot)
{txt}
{com}. *
. *
. *
. * BETWEEN-IDENTITY GROUP DIFFERENTIAL: FIXED STATUS GROUP [SUPERVISORS] PASSIVE REPRESENTATION COVARIATES: [WOMEN SUPERVISORS / MEN SUPERVIORS] &  [MINORITY SUPERVISORS / NON-MINORITY SUPERVISORS]
. gen ln_ratio_fsup_msup         = ln(ratio_fsup_msup)
{txt}
{com}. *
. gen ln_ratio_minsup_nonmsup    = ln(ratio_minsup_nonmsup)
{txt}
{com}. *
. *
. *
. * WITHIN-'OUT-GROUP' STATUS DIFFERENTIAL PASSIVE REPRESENTATION COVARIATES: [WOMEN SUPERVISORS / WOMEN NON-SUPERVISORS] &  [MINORITY SUPERVISORS / MINORITY NON-SUPERVISORS]
. gen ln_ratio_fsup_fsub      = ln(ratio_fsup_fsub)
{txt}
{com}. *
. gen ln_ratio_minsup_minsub  = ln(ratio_minsup_minsub)
{txt}
{com}. *
. *
. *
. * BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL PASSIVE REPRESENTATION COVARIATES: [WOMEN SUPERVISORS / MEN SUPERVISORS] / [WOMEN NON-SUPERVISORS / MEN NON-SUPERVISORS] & [MINORITY SUPERVISORS / NON-MINORITY SUPERVISORS] / [MINORITY NON-SUPERVISORS / NON-MINORITY NON-SUPERVISORS]
. gen ln_ratio_fmsup_fmsub     = ln(ratio_fmsup_fmsub)
{txt}
{com}. *
. gen ln_ratio_mnmsup_mnmsub   = ln(ratio_mnmsup_mnmsub)
{txt}
{com}. *
. *
. *
. * GENERATE LOGGED VERSION OF AGENCY PROFESSIONALISM CONTROL COVARIATE *
. gen ln_professionals_total_ratio  = ln(professionals_total_ratio)
{txt}
{com}.  
. *
. *
. *
. 
. * GENERATE MINORITY WOMEN RESPONSE BINARY INDICATOR (I.E., GENDER ==1 & MINORITY==1)
. gen minority_women = 1 if minority==1 & gender==1
{txt}(2,059,296 missing values generated)

{com}. replace minority_women = 0 if minority_women ==. 
{txt}(2,059,296 real changes made)

{com}. *
. *
. 
. * GENERATE WITHIN SOCIAL-IDENTITY GROUP RESPONDENT HETEROGENEITY TRICHOTMOUS INDICATOR (I.E., MINORITY WOMEN RESPONDENT = 2; WHITE WOMEN/MINORITY MEN RESPONDENT = 1; BASELINE CATEGORY: MEN/NON-MINORITY RESPONDENTS = 0)
. gen     women_het = 2 if gender==1 & minority==1 
{txt}(2,059,296 missing values generated)

{com}. replace women_het = 1 if gender==1 & minority==0 
{txt}(664,266 real changes made)

{com}. replace women_het = 0 if women_het==.
{txt}(1,395,030 real changes made)

{com}. *
. *
. gen     minority_het = 2 if minority==1 & gender==1 
{txt}(2,059,296 missing values generated)

{com}. replace minority_het = 1 if minority==1 & gender==0 
{txt}(410,150 real changes made)

{com}. replace minority_het = 0 if minority_het==. 
{txt}(1,649,146 real changes made)

{com}.  
.  
. 
. ***************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
.  
. 
.  
.  
. 
. **** 1. PRELIMINARY DATA FEATURES *******
. 
. 
. 
. *** TABLE A1: DESCRIPTIVE STATISTIC: BASED ON EFFECTIVE REGRESSION SAMPLES ***
. 
. quietly regress  lndiversity2zeroadj     gender minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)
{txt}
{com}. 
. sum diversity2 lndiversity2zeroadj   justice2  lnjustice2zeroadj         ratio_min_tot_nmin_tot ln_ratio_min_tot_nmin_tot    ratio_fsup_msup  ln_ratio_fsup_msup  ratio_minsup_nonmsup  ln_ratio_minsup_nonmsup ///
> ratio_fsup_fsub  ln_ratio_fsup_fsub   ratio_minsup_minsub  ln_ratio_minsup_minsub   ratio_fmsup_fmsub   ln_ratio_fmsup_fmsub   ratio_mnmsup_mnmsub  ln_ratio_mnmsup_mnmsub  gender minority supervisor  lntotworkforce_count  professionals_total_ratio ln_professionals_total_ratio    topoffgender_2 topoffminority_2 if e(sample), detail

                         {txt}diversity2
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.884637      -2.102011
{txt} 5%    {res}-1.227664      -2.102011
{txt}10%    {res}-.7874214      -2.102011       {txt}Obs         {res}  2,507,103
{txt}25%    {res}-.2984885      -2.102011       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .1531103                      {txt}Mean          {res} .0399574
                        {txt}Largest       Std. dev.     {res} .6356748
{txt}75%    {res} .4702828       .9729975
{txt}90%    {res} .8803418       .9729975       {txt}Variance      {res} .4040825
{txt}95%    {res} .9356537       .9729975       {txt}Skewness      {res}-.8871002
{txt}99%    {res} .9648865       .9729975       {txt}Kurtosis      {res} 3.822486

                     {txt}lndiversity2zeroadj
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.490043       -4.82969
{txt} 5%    {res}-.1251823       -4.82969
{txt}10%    {res} .2795833       -4.82969       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .5941616       -4.82969       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .8167401                      {txt}Mean          {res} .6836906
                        {txt}Largest       Std. dev.     {res} .5252291
{txt}75%    {res}  .947899       1.125902
{txt}90%    {res} 1.095388       1.125902       {txt}Variance      {res} .2758656
{txt}95%    {res} 1.113716       1.125902       {txt}Skewness      {res}-4.557447
{txt}99%    {res} 1.123268       1.125902       {txt}Kurtosis      {res} 35.89936

                          {txt}justice2
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.178193       -2.46851
{txt} 5%    {res}-1.594291       -2.46851
{txt}10%    {res}-1.131444       -2.46851       {txt}Obs         {res}  2,507,103
{txt}25%    {res}-.4026411       -2.46851       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .2027668                      {txt}Mean          {res} .0604981
                        {txt}Largest       Std. dev.     {res} .8223115
{txt}75%    {res} .6280793        1.40478
{txt}90%    {res} 1.073475        1.40478       {txt}Variance      {res} .6761963
{txt}95%    {res} 1.240284        1.40478       {txt}Skewness      {res}-.7184101
{txt}99%    {res} 1.351963        1.40478       {txt}Kurtosis      {res} 3.123875

                      {txt}lnjustice2zeroadj
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.231663      -6.508979
{txt} 5%    {res}-.1327214      -6.508979
{txt}10%    {res} .2915914      -6.508979       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .7262719      -6.508979       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .9831142                      {txt}Mean          {res}  .838005
                        {txt}Largest       Std. dev.     {res} .5338804
{txt}75%    {res} 1.130782       1.354489
{txt}90%    {res} 1.265108       1.354489       {txt}Variance      {res} .2850283
{txt}95%    {res} 1.311108       1.354489       {txt}Skewness      {res} -4.20741
{txt}99%    {res} 1.340764       1.354489       {txt}Kurtosis      {res} 39.74424

                   {txt}ratio_min_tot_nmin_tot
{hline 61}
      Percentiles      Smallest
 1%    {res} .1629806       .0894761
{txt} 5%    {res} .2170546       .0894761
{txt}10%    {res} .3119125       .0894761       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .3972919       .0894761       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .5114757                      {txt}Mean          {res} .6839864
                        {txt}Largest       Std. dev.     {res} .8080838
{txt}75%    {res} .7521186        10.6165
{txt}90%    {res} 1.011676        10.6165       {txt}Variance      {res} .6529995
{txt}95%    {res} 1.174899        10.6165       {txt}Skewness      {res} 7.800785
{txt}99%    {res} 4.365651        10.6165       {txt}Kurtosis      {res} 77.71085

                  {txt}ln_ratio_min_tot_nmin_tot
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.814124      -2.413784
{txt} 5%    {res}-1.527606      -2.413784
{txt}10%    {res}-1.165033      -2.413784       {txt}Obs         {res}  2,507,103
{txt}25%    {res} -.923084      -2.413784       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-.6704552                      {txt}Mean          {res} -.592671
                        {txt}Largest       Std. dev.     {res} .5618937
{txt}75%    {res}-.2848612        2.36241
{txt}90%    {res} .0116086        2.36241       {txt}Variance      {res} .3157246
{txt}95%    {res} .1611818        2.36241       {txt}Skewness      {res} 1.014309
{txt}99%    {res} 1.473767        2.36241       {txt}Kurtosis      {res} 7.183951

                       {txt}ratio_fsup_msup
{hline 61}
      Percentiles      Smallest
 1%    {res} .2191026       .1414474
{txt} 5%    {res} .2528429       .1414474
{txt}10%    {res} .2793682       .1414474       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .3147114       .1414474       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .4686163                      {txt}Mean          {res} .6884398
                        {txt}Largest       Std. dev.     {res} .4621202
{txt}75%    {res} .9989122           2.76
{txt}90%    {res} 1.483684           2.76       {txt}Variance      {res} .2135551
{txt}95%    {res}  1.61227           2.76       {txt}Skewness      {res} .9593516
{txt}99%    {res} 1.764045           2.76       {txt}Kurtosis      {res} 2.678826

                     {txt}ln_ratio_fsup_msup
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.518215      -1.955828
{txt} 5%    {res}-1.374987      -1.955828
{txt}10%    {res}-1.275225      -1.955828       {txt}Obs         {res}  2,507,103
{txt}25%    {res}-1.156099      -1.955828       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} -.757971                      {txt}Mean          {res}-.5834192
                        {txt}Largest       Std. dev.     {res} .6381861
{txt}75%    {res}-.0010884       1.015231
{txt}90%    {res} .3945282       1.015231       {txt}Variance      {res} .4072815
{txt}95%    {res} .4776434       1.015231       {txt}Skewness      {res} .3817928
{txt}99%    {res} .5676094       1.015231       {txt}Kurtosis      {res} 1.732348

                    {txt}ratio_minsup_nonmsup
{hline 61}
      Percentiles      Smallest
 1%    {res} .1137931       .0672783
{txt} 5%    {res}  .180456       .0672783
{txt}10%    {res} .2336135       .0672783       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .2988129       .0672783       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .3557994                      {txt}Mean          {res} .5200464
                        {txt}Largest       Std. dev.     {res} .6909912
{txt}75%    {res} .5578891       9.029703
{txt}90%    {res} .8130297       9.029703       {txt}Variance      {res} .4774689
{txt}95%    {res} .8910292       9.029703       {txt}Skewness      {res} 7.839942
{txt}99%    {res} 3.866667       9.029703       {txt}Kurtosis      {res} 77.71751

                   {txt}ln_ratio_minsup_nonmsup
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.173373      -2.698918
{txt} 5%    {res}-1.712268      -2.698918
{txt}10%    {res}-1.454087      -2.698918       {txt}Obs         {res}  2,507,103
{txt}25%    {res}-1.207938      -2.698918       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-1.033388                      {txt}Mean          {res}-.8944822
                        {txt}Largest       Std. dev.     {res} .5776182
{txt}75%    {res}-.5835952        2.20052
{txt}90%    {res}-.2069877        2.20052       {txt}Variance      {res} .3336428
{txt}95%    {res}-.1153781        2.20052       {txt}Skewness      {res} 1.305467
{txt}99%    {res} 1.352393        2.20052       {txt}Kurtosis      {res} 7.868433

                       {txt}ratio_fsup_fsub
{hline 61}
      Percentiles      Smallest
 1%    {res} .0395093       .0264901
{txt} 5%    {res} .0730134       .0264901
{txt}10%    {res} .0854615       .0264901       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .1008713       .0264901       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}  .116787                      {txt}Mean          {res} .1222929
                        {txt}Largest       Std. dev.     {res} .0385203
{txt}75%    {res} .1352793       .3721264
{txt}90%    {res} .1818267       .3721264       {txt}Variance      {res} .0014838
{txt}95%    {res} .1961538       .3721264       {txt}Skewness      {res} 1.068487
{txt}99%    {res} .2330097       .3721264       {txt}Kurtosis      {res}  6.16013

                     {txt}ln_ratio_fsup_fsub
{hline 61}
      Percentiles      Smallest
 1%    {res}-3.231219      -3.630985
{txt} 5%    {res}-2.617113      -3.630985
{txt}10%    {res} -2.45969      -3.630985       {txt}Obs         {res}  2,507,103
{txt}25%    {res} -2.29391      -3.630985       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-2.147403                      {txt}Mean          {res}-2.150777
                        {txt}Largest       Std. dev.     {res}  .322378
{txt}75%    {res}-2.000413      -.9885217
{txt}90%    {res}-1.704701      -.9885217       {txt}Variance      {res} .1039276
{txt}95%    {res}-1.628856      -.9885217       {txt}Skewness      {res}  -.61638
{txt}99%    {res}-1.456675      -.9885217       {txt}Kurtosis      {res}  5.26209

                     {txt}ratio_minsup_minsub
{hline 61}
      Percentiles      Smallest
 1%    {res} .0295114       .0251511
{txt} 5%    {res} .0635253       .0251511
{txt}10%    {res} .0768116       .0251511       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .0976919       .0251511       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .1169809                      {txt}Mean          {res} .1209973
                        {txt}Largest       Std. dev.     {res} .0409263
{txt}75%    {res} .1404839       .2962206
{txt}90%    {res} .1747593       .2962206       {txt}Variance      {res}  .001675
{txt}95%    {res} .1940909       .2962206       {txt}Skewness      {res} 1.003314
{txt}99%    {res} .2751684       .2962206       {txt}Kurtosis      {res} 5.455517

                   {txt}ln_ratio_minsup_minsub
{hline 61}
      Percentiles      Smallest
 1%    {res} -3.52298      -3.682852
{txt} 5%    {res}-2.756317      -3.682852
{txt}10%    {res}  -2.5664      -3.682852       {txt}Obs         {res}  2,507,103
{txt}25%    {res}-2.325937      -3.682852       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-2.145745                      {txt}Mean          {res}-2.170633
                        {txt}Largest       Std. dev.     {res} .3557334
{txt}75%    {res}-1.962663      -1.216651
{txt}90%    {res}-1.744346      -1.216651       {txt}Variance      {res} .1265462
{txt}95%    {res}-1.639429      -1.216651       {txt}Skewness      {res}-.8360496
{txt}99%    {res}-1.290372      -1.216651       {txt}Kurtosis      {res}  5.85637

                      {txt}ratio_fmsup_fmsub
{hline 61}
      Percentiles      Smallest
 1%    {res}  .447435       .2087663
{txt} 5%    {res} .5116068       .2087663
{txt}10%    {res}  .569413       .2087663       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .6051247       .2087663       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .7184923                      {txt}Mean          {res} .7147444
                        {txt}Largest       Std. dev.     {res} .1330109
{txt}75%    {res}   .79542       1.288136
{txt}90%    {res} .8804573       1.288136       {txt}Variance      {res} .0176919
{txt}95%    {res} .9350842       1.288136       {txt}Skewness      {res} .2093074
{txt}99%    {res} 1.023452       1.288136       {txt}Kurtosis      {res} 3.746474

                    {txt}ln_ratio_fmsup_fmsub
{hline 61}
      Percentiles      Smallest
 1%    {res}-.8042241       -1.56654
{txt} 5%    {res}-.6701989       -1.56654
{txt}10%    {res}-.5631493       -1.56654       {txt}Obs         {res}  2,507,103
{txt}25%    {res}-.5023206       -1.56654       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-.3306003                      {txt}Mean          {res}-.3539487
                        {txt}Largest       Std. dev.     {res} .1943215
{txt}75%    {res} -.228885       .2531959
{txt}90%    {res}-.1273139       .2531959       {txt}Variance      {res} .0377608
{txt}95%    {res}-.0671187       .2531959       {txt}Skewness      {res}-.7444688
{txt}99%    {res} .0231811       .2531959       {txt}Kurtosis      {res} 5.963143

                     {txt}ratio_mnmsup_mnmsub
{hline 61}
      Percentiles      Smallest
 1%    {res} .3743393       .2083137
{txt} 5%    {res} .4728143       .2083137
{txt}10%    {res} .5799614       .2083137       {txt}Obs         {res}  2,507,103
{txt}25%    {res} .6630492       .2083137       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .7148632                      {txt}Mean          {res}   .72322
                        {txt}Largest       Std. dev.     {res} .1445182
{txt}75%    {res}  .797907        1.66013
{txt}90%    {res} .8660599        1.66013       {txt}Variance      {res} .0208855
{txt}95%    {res} .9347755        1.66013       {txt}Skewness      {res} 1.259672
{txt}99%    {res} 1.256523        1.66013       {txt}Kurtosis      {res} 10.56668

                   {txt}ln_ratio_mnmsup_mnmsub
{hline 61}
      Percentiles      Smallest
 1%    {res}-.9825926       -1.56871
{txt} 5%    {res}-.7490525       -1.56871
{txt}10%    {res}-.5447937       -1.56871       {txt}Obs         {res}  2,507,103
{txt}25%    {res} -.410906       -1.56871       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-.3356641                      {txt}Mean          {res}-.3435455
                        {txt}Largest       Std. dev.     {res} .1996111
{txt}75%    {res}-.2257632       .5068959
{txt}90%    {res}-.1438013       .5068959       {txt}Variance      {res} .0398446
{txt}95%    {res}-.0674489       .5068959       {txt}Skewness      {res}-.4813639
{txt}99%    {res} .2283484       .5068959       {txt}Kurtosis      {res} 6.272329

                           {txt}gender
{hline 61}
      Percentiles      Smallest
 1%    {res}        0              0
{txt} 5%    {res}        0              0
{txt}10%    {res}        0              0       {txt}Obs         {res}  2,507,103
{txt}25%    {res}        0              0       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}        0                      {txt}Mean          {res} .4435689
                        {txt}Largest       Std. dev.     {res} .4968054
{txt}75%    {res}        1              1
{txt}90%    {res}        1              1       {txt}Variance      {res} .2468156
{txt}95%    {res}        1              1       {txt}Skewness      {res} .2271758
{txt}99%    {res}        1              1       {txt}Kurtosis      {res} 1.051609

                          {txt}minority
{hline 61}
      Percentiles      Smallest
 1%    {res}        0              0
{txt} 5%    {res}        0              0
{txt}10%    {res}        0              0       {txt}Obs         {res}  2,507,103
{txt}25%    {res}        0              0       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}        0                      {txt}Mean          {res} .3422105
                        {txt}Largest       Std. dev.     {res} .4744498
{txt}75%    {res}        1              1
{txt}90%    {res}        1              1       {txt}Variance      {res} .2251026
{txt}95%    {res}        1              1       {txt}Skewness      {res} .6651474
{txt}99%    {res}        1              1       {txt}Kurtosis      {res} 1.442421

                         {txt}supervisor
{hline 61}
      Percentiles      Smallest
 1%    {res}        0              0
{txt} 5%    {res}        0              0
{txt}10%    {res}        0              0       {txt}Obs         {res}  2,507,103
{txt}25%    {res}        0              0       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}        0                      {txt}Mean          {res} .2439688
                        {txt}Largest       Std. dev.     {res} .4294742
{txt}75%    {res}        0              1
{txt}90%    {res}        1              1       {txt}Variance      {res} .1844481
{txt}95%    {res}        1              1       {txt}Skewness      {res} 1.192301
{txt}99%    {res}        1              1       {txt}Kurtosis      {res} 2.421581

                    {txt}lntotworkforce_count
{hline 61}
      Percentiles      Smallest
 1%    {res} 7.148346       6.481577
{txt} 5%    {res} 7.964503       6.481577
{txt}10%    {res} 8.497399       6.481577       {txt}Obs         {res}  2,507,103
{txt}25%    {res} 9.351493       6.481577       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} 10.54555                      {txt}Mean          {res} 10.45253
                        {txt}Largest       Std. dev.     {res}  1.50003
{txt}75%    {res} 12.03991         12.743
{txt}90%    {res}  12.4409         12.743       {txt}Variance      {res}  2.25009
{txt}95%    {res} 12.54842         12.743       {txt}Skewness      {res}-.1759878
{txt}99%    {res}   12.743         12.743       {txt}Kurtosis      {res} 2.055077

                  {txt}professionals_total_ratio
{hline 61}
      Percentiles      Smallest
 1%    {res} .0065487       .0016456
{txt} 5%    {res} .0228254       .0016456
{txt}10%    {res} .0578553       .0016456       {txt}Obs         {res}  2,507,103
{txt}25%    {res}  .111412       .0016456       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res} .2270951                      {txt}Mean          {res} .2664368
                        {txt}Largest       Std. dev.     {res} .2012644
{txt}75%    {res} .3858082       .8992231
{txt}90%    {res} .5845588       .8992231       {txt}Variance      {res} .0405073
{txt}95%    {res} .6863896       .8992231       {txt}Skewness      {res} 1.015528
{txt}99%    {res} .8392715       .8992231       {txt}Kurtosis      {res}  3.31975

                {txt}ln_professionals_total_ratio
{hline 61}
      Percentiles      Smallest
 1%    {res}-5.028493      -6.409626
{txt} 5%    {res}-3.779881      -6.409626
{txt}10%    {res}-2.849809      -6.409626       {txt}Obs         {res}  2,507,103
{txt}25%    {res} -2.19452      -6.409626       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}-1.482386                      {txt}Mean          {res}-1.699252
                        {txt}Largest       Std. dev.     {res} 1.031838
{txt}75%    {res}-.9524149      -.1062241
{txt}90%    {res}-.5368979      -.1062241       {txt}Variance      {res}  1.06469
{txt}95%    {res}-.3763099      -.1062241       {txt}Skewness      {res}-1.275891
{txt}99%    {res} -.175221      -.1062241       {txt}Kurtosis      {res} 5.097191

                       {txt}topoffgender_2
{hline 61}
      Percentiles      Smallest
 1%    {res}        0              0
{txt} 5%    {res}        0              0
{txt}10%    {res}        0              0       {txt}Obs         {res}  2,507,103
{txt}25%    {res}        0              0       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}        0                      {txt}Mean          {res} .1874769
                        {txt}Largest       Std. dev.     {res}  .390294
{txt}75%    {res}        0              1
{txt}90%    {res}        1              1       {txt}Variance      {res} .1523294
{txt}95%    {res}        1              1       {txt}Skewness      {res} 1.601475
{txt}99%    {res}        1              1       {txt}Kurtosis      {res} 3.564724

                      {txt}topoffminority_2
{hline 61}
      Percentiles      Smallest
 1%    {res}        0              0
{txt} 5%    {res}        0              0
{txt}10%    {res}        0              0       {txt}Obs         {res}  2,507,103
{txt}25%    {res}        0              0       {txt}Sum of wgt. {res}  2,507,103

{txt}50%    {res}        0                      {txt}Mean          {res} .1985634
                        {txt}Largest       Std. dev.     {res} .3989186
{txt}75%    {res}        0              1
{txt}90%    {res}        1              1       {txt}Variance      {res} .1591361
{txt}95%    {res}        1              1       {txt}Skewness      {res} 1.511269
{txt}99%    {res}        1              1       {txt}Kurtosis      {res} 3.283933
{txt}
{com}. *
. tab gender  if e(sample)

     {txt}gender {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}  1,395,030       55.64       55.64
{txt}          1 {c |}{res}  1,112,073       44.36      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}  2,507,103      100.00
{txt}
{com}. tab minority if e(sample)

   {txt}minority {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}  1,649,146       65.78       65.78
{txt}          1 {c |}{res}    857,957       34.22      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}  2,507,103      100.00
{txt}
{com}. *
. tab gender minority if e(sample)

           {txt}{c |}       minority
    gender {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}   984,880    410,150 {txt}{c |}{res} 1,395,030 
{txt}         1 {c |}{res}   664,266    447,807 {txt}{c |}{res} 1,112,073 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res} 1,649,146    857,957 {txt}{c |}{res} 2,507,103 
{txt}
{com}. tab minority_women if e(sample)

{txt}minority_wo {c |}
        men {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}  2,059,296       82.14       82.14
{txt}          1 {c |}{res}    447,807       17.86      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}  2,507,103      100.00
{txt}
{com}. *
. tab women_het if e(sample)

  {txt}women_het {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}  1,395,030       55.64       55.64
{txt}          1 {c |}{res}    664,266       26.50       82.14
{txt}          2 {c |}{res}    447,807       17.86      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}  2,507,103      100.00
{txt}
{com}. tab minority_het if e(sample)

{txt}minority_he {c |}
          t {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}  1,649,146       65.78       65.78
{txt}          1 {c |}{res}    410,150       16.36       82.14
{txt}          2 {c |}{res}    447,807       17.86      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}  2,507,103      100.00
{txt}
{com}. *
. *
. *
. tab supervisor if e(sample)

 {txt}supervisor {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}  1,895,448       75.60       75.60
{txt}          1 {c |}{res}    611,655       24.40      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}  2,507,103      100.00
{txt}
{com}. *
. *
. tab gender supervisor if e(sample)

           {txt}{c |}      supervisor
    gender {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res} 1,002,633    392,397 {txt}{c |}{res} 1,395,030 
{txt}         1 {c |}{res}   892,815    219,258 {txt}{c |}{res} 1,112,073 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res} 1,895,448    611,655 {txt}{c |}{res} 2,507,103 
{txt}
{com}. tab minority supervisor if e(sample)

           {txt}{c |}      supervisor
  minority {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res} 1,209,318    439,828 {txt}{c |}{res} 1,649,146 
{txt}         1 {c |}{res}   686,130    171,827 {txt}{c |}{res}   857,957 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res} 1,895,448    611,655 {txt}{c |}{res} 2,507,103 
{txt}
{com}. *
. *
. 
. 
. 
.    
. *** MANUSCRIPT NOTES: SIMPLE BIVRIATE CORRELATIONS AMONG OVERALL PR, SUPERVISORY PR, ABSOLUTE SGPD, & RELATIVE SGPD MEASURES (BOTH LEVELS AND NATURAL LOGARITHM FORMATS) ***   
. 
. 
. *** EVALUATE SIMILARITIES/DISSIMILARITIES AMONG ALTERNATIVE MEASURES OF DESCRIPTIVE REPRESENTATION WITHIN U.S. FEDERAL AGENCIES ***
. 
. 
. *** VARIABLES OPERATIONALIZED IN LEVELS ***
. 
. correlate ratio_fem_tot_men_tot    ratio_fsup_msup   ratio_fsup_fsub   ratio_fmsup_fmsub 
{txt}(obs=2,507,103)

             {c |} r~en_tot ra~_msup rat~fsub ra~fmsub
{hline 13}{c +}{hline 36}
ratio_fem_~t {c |}{res}   1.0000
{txt}ratio_fsup~p {c |}{res}   0.9556   1.0000
{txt}ratio_fsup~b {c |}{res}  -0.2902  -0.1822   1.0000
{txt}ratio_fmsu~b {c |}{res}   0.0142   0.2616   0.3148   1.0000

{txt}
{com}. *
. correlate ratio_min_tot_nmin_tot  ratio_minsup_nonmsup   ratio_minsup_minsub   ratio_mnmsup_mnmsub
{txt}(obs=2,507,103)

             {c |} r~in_tot ra~nmsup rat~nsub r~mnmsub
{hline 13}{c +}{hline 36}
ratio_min_~t {c |}{res}   1.0000
{txt}ratio_mins~p {c |}{res}   0.9898   1.0000
{txt}ratio_m~nsub {c |}{res}  -0.0315   0.0149   1.0000
{txt}ratio_mnms~b {c |}{res}   0.0599   0.1656   0.3712   1.0000

{txt}
{com}. 
. 
. 
. *** VARIABLES OPERATIONALIZED IN NATURAL LOGARITHMS [REDUCE SKEW AND KURTOSIS] ***
. 
. correlate  ln_ratio_fem_tot_men_tot   ln_ratio_fsup_msup         ln_ratio_fsup_fsub      ln_ratio_fmsup_fmsub
{txt}(obs=2,507,103)

             {c |} l~en_tot ln~_msup ln_~fsub ln~fmsub
{hline 13}{c +}{hline 36}
ln_ratio_f~t {c |}{res}   1.0000
{txt}ln_ratio_f~p {c |}{res}   0.9643   1.0000
{txt}ln_rati~fsub {c |}{res}  -0.3587  -0.2374   1.0000
{txt}ln_rat~fmsub {c |}{res}  -0.0468   0.2180   0.3573   1.0000

{txt}
{com}. *
. correlate  ln_ratio_min_tot_nmin_tot  ln_ratio_minsup_nonmsup    ln_ratio_minsup_minsub   ln_ratio_mnmsup_mnmsub
{txt}(obs=2,507,103)

             {c |} l~in_tot ln~nmsup ln_~nsub ln~nmsub
{hline 13}{c +}{hline 36}
ln_ratio_m~t {c |}{res}   1.0000
{txt}ln_ratio_m~p {c |}{res}   0.9513   1.0000
{txt}ln_rati~nsub {c |}{res}  -0.1256   0.0364   1.0000
{txt}ln_rat~nmsub {c |}{res}  -0.0660   0.2436   0.4480   1.0000

{txt}
{com}. 
. 
. 
. *** TAKEAWAYS: (1) OVERALL PR AND SUPERVISORY PR MEASURES ARE STRONGLY CORRLATED AND THUS PICKING UP THE SAME DESCRIPTIVE REPRESENTATION CONCEPT WITH THESE SAMPLE OF DATA ***
. ***     (2) ABSOLUTE AND RELATIVE SGPD MEASURES ARE MODERATELY CORRELATED -- BUT SUFFICIENTLY DISTINCT MEASURES -- MAKES SENSE SINCE FORMER MEASURE IS "NUMERATOR" OF LATTER MEASURE
. ***     (3) ABSOLUTE AND RELATIVE SGPD MEASURES ARE OFTEN WEAKLY CORRELATED WITH OVERALL & SUPERVISORY PR MEASURES -- MEANS THAT SGPD MEASURES ARE CLEARLY DISTINCT FROM PR MEASURES    
.  
.  
.  
. ********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
.    
. *** 2. TABLE A1: CONDITIONAL-RESPONDENT MODELS EVALUATING THE RELATIONSHIP INVOLVING WITHIN-IDENTITY "OUT-GROUP" STATUS & BETWEEN-IDENTITY GROUP STATUS DIFFERENTIALS AS A MEANS TO FOSTER DIVERSITY AND INCLUSION IN THE U.S. CIVILIAN WORKFORCE ***   
. 
. 
. 
. *********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
.    
. *** MODEL 1: CONDITIONAL RESPONSES BY GENDER -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS  WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. 
. regress lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.gender  ln_ratio_fem_tot_men_tot  minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(17, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0404
                                                {txt}Root MSE          =    {res} .51453

{txt}{ralign 95:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}          lndiversity2zeroadj{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ln_ratio_fmsup_fmsub {c |}{col 31}{res}{space 2} .1524577{col 43}{space 2} .0417215{col 54}{space 1}    3.65{col 63}{space 3}0.000{col 71}{space 4} .0697225{col 84}{space 3}  .235193
{txt}{space 21}1.gender {c |}{col 31}{res}{space 2}-.0396382{col 43}{space 2} .0065298{col 54}{space 1}   -6.07{col 63}{space 3}0.000{col 71}{space 4} -.052587{col 84}{space 3}-.0266894
{txt}{space 29} {c |}
gender#c.ln_ratio_fmsup_fmsub {c |}
{space 27}1  {c |}{col 31}{res}{space 2}-.0001655{col 43}{space 2} .0193692{col 54}{space 1}   -0.01{col 63}{space 3}0.993{col 71}{space 4}-.0385754{col 84}{space 3} .0382443
{txt}{space 29} {c |}
{space 5}ln_ratio_fem_tot_men_tot {c |}{col 31}{res}{space 2}-.0055401{col 43}{space 2} .0554533{col 54}{space 1}   -0.10{col 63}{space 3}0.921{col 71}{space 4} -.115506{col 84}{space 3} .1044258
{txt}{space 21}minority {c |}{col 31}{res}{space 2}-.0944581{col 43}{space 2} .0037842{col 54}{space 1}  -24.96{col 63}{space 3}0.000{col 71}{space 4}-.1019624{col 84}{space 3}-.0869539
{txt}{space 19}supervisor {c |}{col 31}{res}{space 2} .1271158{col 43}{space 2} .0074357{col 54}{space 1}   17.10{col 63}{space 3}0.000{col 71}{space 4} .1123705{col 84}{space 3} .1418611
{txt}{space 15}topoffgender_2 {c |}{col 31}{res}{space 2}-.0028393{col 43}{space 2} .0044962{col 54}{space 1}   -0.63{col 63}{space 3}0.529{col 71}{space 4}-.0117555{col 84}{space 3} .0060768
{txt}{space 9}lntotworkforce_count {c |}{col 31}{res}{space 2} .0752857{col 43}{space 2} .0323927{col 54}{space 1}    2.32{col 63}{space 3}0.022{col 71}{space 4} .0110498{col 84}{space 3} .1395217
{txt}{space 1}ln_professionals_total_ratio {c |}{col 31}{res}{space 2} .0080096{col 43}{space 2} .0415357{col 54}{space 1}    0.19{col 63}{space 3}0.847{col 71}{space 4}-.0743572{col 84}{space 3} .0903765
{txt}{space 29} {c |}
{space 21}agencyid {c |}
{space 27}2  {c |}{col 31}{res}{space 2} .3068933{col 43}{space 2} .1145586{col 54}{space 1}    2.68{col 63}{space 3}0.009{col 71}{space 4} .0797193{col 84}{space 3} .5340673
{txt}{space 27}3  {c |}{col 31}{res}{space 2} .0908724{col 43}{space 2} .0541133{col 54}{space 1}    1.68{col 63}{space 3}0.096{col 71}{space 4}-.0164364{col 84}{space 3} .1981812
{txt}{space 27}4  {c |}{col 31}{res}{space 2} .4343055{col 43}{space 2} .1510661{col 54}{space 1}    2.87{col 63}{space 3}0.005{col 71}{space 4} .1347357{col 84}{space 3} .7338753
{txt}{space 27}5  {c |}{col 31}{res}{space 2} .2626169{col 43}{space 2} .1045647{col 54}{space 1}    2.51{col 63}{space 3}0.014{col 71}{space 4} .0552612{col 84}{space 3} .4699727
{txt}{space 27}6  {c |}{col 31}{res}{space 2} .2488859{col 43}{space 2} .1105814{col 54}{space 1}    2.25{col 63}{space 3}0.027{col 71}{space 4} .0295989{col 84}{space 3} .4681729
{txt}{space 27}7  {c |}{col 31}{res}{space 2} .3553129{col 43}{space 2} .1826609{col 54}{space 1}    1.95{col 63}{space 3}0.054{col 71}{space 4}-.0069106{col 84}{space 3} .7175364
{txt}{space 27}8  {c |}{col 31}{res}{space 2} .3012061{col 43}{space 2} .1426286{col 54}{space 1}    2.11{col 63}{space 3}0.037{col 71}{space 4} .0183683{col 84}{space 3} .5840439
{txt}{space 27}9  {c |}{col 31}{res}{space 2} -.012014{col 43}{space 2} .0226551{col 54}{space 1}   -0.53{col 63}{space 3}0.597{col 71}{space 4}-.0569399{col 84}{space 3} .0329119
{txt}{space 26}10  {c |}{col 31}{res}{space 2} .2507442{col 43}{space 2}  .161674{col 54}{space 1}    1.55{col 63}{space 3}0.124{col 71}{space 4}-.0698615{col 84}{space 3} .5713498
{txt}{space 26}11  {c |}{col 31}{res}{space 2} .2144846{col 43}{space 2} .1179771{col 54}{space 1}    1.82{col 63}{space 3}0.072{col 71}{space 4}-.0194684{col 84}{space 3} .4484376
{txt}{space 26}12  {c |}{col 31}{res}{space 2} .3736679{col 43}{space 2} .1713569{col 54}{space 1}    2.18{col 63}{space 3}0.031{col 71}{space 4} .0338608{col 84}{space 3} .7134751
{txt}{space 26}13  {c |}{col 31}{res}{space 2} .3569291{col 43}{space 2} .1437543{col 54}{space 1}    2.48{col 63}{space 3}0.015{col 71}{space 4}  .071859{col 84}{space 3} .6419992
{txt}{space 26}14  {c |}{col 31}{res}{space 2} .1616699{col 43}{space 2} .1056181{col 54}{space 1}    1.53{col 63}{space 3}0.129{col 71}{space 4}-.0477747{col 84}{space 3} .3711144
{txt}{space 26}15  {c |}{col 31}{res}{space 2} .3018322{col 43}{space 2} .1163951{col 54}{space 1}    2.59{col 63}{space 3}0.011{col 71}{space 4} .0710163{col 84}{space 3} .5326481
{txt}{space 26}16  {c |}{col 31}{res}{space 2} .4704568{col 43}{space 2} .1971816{col 54}{space 1}    2.39{col 63}{space 3}0.019{col 71}{space 4} .0794383{col 84}{space 3} .8614753
{txt}{space 26}17  {c |}{col 31}{res}{space 2} .1311255{col 43}{space 2} .1576681{col 54}{space 1}    0.83{col 63}{space 3}0.408{col 71}{space 4}-.1815362{col 84}{space 3} .4437873
{txt}{space 26}18  {c |}{col 31}{res}{space 2} .3550958{col 43}{space 2}  .152628{col 54}{space 1}    2.33{col 63}{space 3}0.022{col 71}{space 4} .0524287{col 84}{space 3} .6577628
{txt}{space 26}19  {c |}{col 31}{res}{space 2} .2224404{col 43}{space 2} .0986771{col 54}{space 1}    2.25{col 63}{space 3}0.026{col 71}{space 4}   .02676{col 84}{space 3} .4181207
{txt}{space 26}20  {c |}{col 31}{res}{space 2} .2984723{col 43}{space 2} .1586092{col 54}{space 1}    1.88{col 63}{space 3}0.063{col 71}{space 4}-.0160557{col 84}{space 3} .6130002
{txt}{space 26}21  {c |}{col 31}{res}{space 2} .2688482{col 43}{space 2} .1191367{col 54}{space 1}    2.26{col 63}{space 3}0.026{col 71}{space 4} .0325958{col 84}{space 3} .5051007
{txt}{space 26}22  {c |}{col 31}{res}{space 2} .2686394{col 43}{space 2} .1438159{col 54}{space 1}    1.87{col 63}{space 3}0.065{col 71}{space 4}-.0165528{col 84}{space 3} .5538317
{txt}{space 26}23  {c |}{col 31}{res}{space 2}-.0831314{col 43}{space 2} .0511335{col 54}{space 1}   -1.63{col 63}{space 3}0.107{col 71}{space 4}-.1845309{col 84}{space 3} .0182682
{txt}{space 26}24  {c |}{col 31}{res}{space 2} .2937881{col 43}{space 2} .0962149{col 54}{space 1}    3.05{col 63}{space 3}0.003{col 71}{space 4} .1029904{col 84}{space 3} .4845858
{txt}{space 26}25  {c |}{col 31}{res}{space 2} .1982798{col 43}{space 2} .1352139{col 54}{space 1}    1.47{col 63}{space 3}0.146{col 71}{space 4}-.0698545{col 84}{space 3}  .466414
{txt}{space 26}26  {c |}{col 31}{res}{space 2} .1028711{col 43}{space 2} .1110906{col 54}{space 1}    0.93{col 63}{space 3}0.357{col 71}{space 4}-.1174258{col 84}{space 3}  .323168
{txt}{space 26}27  {c |}{col 31}{res}{space 2} .3884928{col 43}{space 2} .1579821{col 54}{space 1}    2.46{col 63}{space 3}0.016{col 71}{space 4} .0752084{col 84}{space 3} .7017773
{txt}{space 26}28  {c |}{col 31}{res}{space 2} .0052087{col 43}{space 2} .0729082{col 54}{space 1}    0.07{col 63}{space 3}0.943{col 71}{space 4}-.1393711{col 84}{space 3} .1497885
{txt}{space 26}29  {c |}{col 31}{res}{space 2} .1098802{col 43}{space 2} .1309587{col 54}{space 1}    0.84{col 63}{space 3}0.403{col 71}{space 4}-.1498158{col 84}{space 3} .3695762
{txt}{space 26}30  {c |}{col 31}{res}{space 2} .1446672{col 43}{space 2} .1218317{col 54}{space 1}    1.19{col 63}{space 3}0.238{col 71}{space 4}-.0969297{col 84}{space 3} .3862641
{txt}{space 26}31  {c |}{col 31}{res}{space 2}-.0110762{col 43}{space 2}  .146067{col 54}{space 1}   -0.08{col 63}{space 3}0.940{col 71}{space 4}-.3007325{col 84}{space 3}   .27858
{txt}{space 26}32  {c |}{col 31}{res}{space 2} .2514609{col 43}{space 2} .1132503{col 54}{space 1}    2.22{col 63}{space 3}0.029{col 71}{space 4} .0268814{col 84}{space 3} .4760404
{txt}{space 26}33  {c |}{col 31}{res}{space 2} .1519061{col 43}{space 2} .0692259{col 54}{space 1}    2.19{col 63}{space 3}0.030{col 71}{space 4} .0146286{col 84}{space 3} .2891836
{txt}{space 26}34  {c |}{col 31}{res}{space 2} .1474427{col 43}{space 2} .1202989{col 54}{space 1}    1.23{col 63}{space 3}0.223{col 71}{space 4}-.0911146{col 84}{space 3}     .386
{txt}{space 26}35  {c |}{col 31}{res}{space 2}  .186925{col 43}{space 2} .0941124{col 54}{space 1}    1.99{col 63}{space 3}0.050{col 71}{space 4} .0002966{col 84}{space 3} .3735534
{txt}{space 26}36  {c |}{col 31}{res}{space 2} .2438425{col 43}{space 2} .1180871{col 54}{space 1}    2.06{col 63}{space 3}0.041{col 71}{space 4} .0096713{col 84}{space 3} .4780137
{txt}{space 26}37  {c |}{col 31}{res}{space 2} .2397496{col 43}{space 2} .1117387{col 54}{space 1}    2.15{col 63}{space 3}0.034{col 71}{space 4} .0181676{col 84}{space 3} .4613315
{txt}{space 26}38  {c |}{col 31}{res}{space 2} .3888059{col 43}{space 2} .1633713{col 54}{space 1}    2.38{col 63}{space 3}0.019{col 71}{space 4} .0648346{col 84}{space 3} .7127773
{txt}{space 26}39  {c |}{col 31}{res}{space 2} .2152301{col 43}{space 2} .1156308{col 54}{space 1}    1.86{col 63}{space 3}0.066{col 71}{space 4}-.0140701{col 84}{space 3} .4445303
{txt}{space 26}40  {c |}{col 31}{res}{space 2} .0308496{col 43}{space 2}  .072041{col 54}{space 1}    0.43{col 63}{space 3}0.669{col 71}{space 4}-.1120105{col 84}{space 3} .1737097
{txt}{space 26}41  {c |}{col 31}{res}{space 2}  .303505{col 43}{space 2} .1478692{col 54}{space 1}    2.05{col 63}{space 3}0.043{col 71}{space 4}  .010275{col 84}{space 3} .5967351
{txt}{space 26}42  {c |}{col 31}{res}{space 2} .3187382{col 43}{space 2} .1221542{col 54}{space 1}    2.61{col 63}{space 3}0.010{col 71}{space 4} .0765019{col 84}{space 3} .5609745
{txt}{space 26}43  {c |}{col 31}{res}{space 2} .1074205{col 43}{space 2} .0476018{col 54}{space 1}    2.26{col 63}{space 3}0.026{col 71}{space 4} .0130244{col 84}{space 3} .2018166
{txt}{space 26}44  {c |}{col 31}{res}{space 2} .3525377{col 43}{space 2} .1033483{col 54}{space 1}    3.41{col 63}{space 3}0.001{col 71}{space 4} .1475943{col 84}{space 3} .5574812
{txt}{space 26}45  {c |}{col 31}{res}{space 2}  .301771{col 43}{space 2} .1230257{col 54}{space 1}    2.45{col 63}{space 3}0.016{col 71}{space 4} .0578063{col 84}{space 3} .5457357
{txt}{space 26}46  {c |}{col 31}{res}{space 2} .2825887{col 43}{space 2}  .187495{col 54}{space 1}    1.51{col 63}{space 3}0.135{col 71}{space 4} -.089221{col 84}{space 3} .6543984
{txt}{space 26}47  {c |}{col 31}{res}{space 2} .2053489{col 43}{space 2} .0864226{col 54}{space 1}    2.38{col 63}{space 3}0.019{col 71}{space 4} .0339696{col 84}{space 3} .3767282
{txt}{space 26}48  {c |}{col 31}{res}{space 2} .2315361{col 43}{space 2} .1337703{col 54}{space 1}    1.73{col 63}{space 3}0.086{col 71}{space 4}-.0337355{col 84}{space 3} .4968077
{txt}{space 26}49  {c |}{col 31}{res}{space 2}  .445472{col 43}{space 2} .1922026{col 54}{space 1}    2.32{col 63}{space 3}0.022{col 71}{space 4} .0643271{col 84}{space 3}  .826617
{txt}{space 26}50  {c |}{col 31}{res}{space 2} .4210377{col 43}{space 2} .1596375{col 54}{space 1}    2.64{col 63}{space 3}0.010{col 71}{space 4} .1044706{col 84}{space 3} .7376048
{txt}{space 26}51  {c |}{col 31}{res}{space 2} .3729112{col 43}{space 2} .1906501{col 54}{space 1}    1.96{col 63}{space 3}0.053{col 71}{space 4}-.0051551{col 84}{space 3} .7509774
{txt}{space 26}52  {c |}{col 31}{res}{space 2} .3355159{col 43}{space 2} .1824077{col 54}{space 1}    1.84{col 63}{space 3}0.069{col 71}{space 4}-.0262055{col 84}{space 3} .6972372
{txt}{space 26}53  {c |}{col 31}{res}{space 2} .3015947{col 43}{space 2} .1356633{col 54}{space 1}    2.22{col 63}{space 3}0.028{col 71}{space 4} .0325693{col 84}{space 3}   .57062
{txt}{space 26}54  {c |}{col 31}{res}{space 2} .3428167{col 43}{space 2} .1533333{col 54}{space 1}    2.24{col 63}{space 3}0.028{col 71}{space 4}  .038751{col 84}{space 3} .6468824
{txt}{space 26}55  {c |}{col 31}{res}{space 2} .5349055{col 43}{space 2} .2136089{col 54}{space 1}    2.50{col 63}{space 3}0.014{col 71}{space 4} .1113111{col 84}{space 3} .9584998
{txt}{space 26}56  {c |}{col 31}{res}{space 2} .2986947{col 43}{space 2} .1997431{col 54}{space 1}    1.50{col 63}{space 3}0.138{col 71}{space 4}-.0974033{col 84}{space 3} .6947927
{txt}{space 26}57  {c |}{col 31}{res}{space 2} .4072206{col 43}{space 2} .2309467{col 54}{space 1}    1.76{col 63}{space 3}0.081{col 71}{space 4}-.0507554{col 84}{space 3} .8651965
{txt}{space 26}58  {c |}{col 31}{res}{space 2} .2953686{col 43}{space 2} .1509924{col 54}{space 1}    1.96{col 63}{space 3}0.053{col 71}{space 4}-.0040549{col 84}{space 3} .5947921
{txt}{space 26}59  {c |}{col 31}{res}{space 2} .3375406{col 43}{space 2} .1708001{col 54}{space 1}    1.98{col 63}{space 3}0.051{col 71}{space 4}-.0011623{col 84}{space 3} .6762435
{txt}{space 26}60  {c |}{col 31}{res}{space 2} .1820469{col 43}{space 2} .0934949{col 54}{space 1}    1.95{col 63}{space 3}0.054{col 71}{space 4}-.0033569{col 84}{space 3} .3674507
{txt}{space 26}61  {c |}{col 31}{res}{space 2} .1848526{col 43}{space 2}  .106568{col 54}{space 1}    1.73{col 63}{space 3}0.086{col 71}{space 4}-.0264758{col 84}{space 3}  .396181
{txt}{space 26}62  {c |}{col 31}{res}{space 2}  .394459{col 43}{space 2} .1732431{col 54}{space 1}    2.28{col 63}{space 3}0.025{col 71}{space 4} .0509115{col 84}{space 3} .7380065
{txt}{space 26}63  {c |}{col 31}{res}{space 2} .4559771{col 43}{space 2} .1713963{col 54}{space 1}    2.66{col 63}{space 3}0.009{col 71}{space 4} .1160919{col 84}{space 3} .7958623
{txt}{space 26}64  {c |}{col 31}{res}{space 2} .4582278{col 43}{space 2} .1865658{col 54}{space 1}    2.46{col 63}{space 3}0.016{col 71}{space 4} .0882609{col 84}{space 3} .8281947
{txt}{space 26}65  {c |}{col 31}{res}{space 2} .2712253{col 43}{space 2}  .102782{col 54}{space 1}    2.64{col 63}{space 3}0.010{col 71}{space 4} .0674047{col 84}{space 3} .4750459
{txt}{space 26}66  {c |}{col 31}{res}{space 2} .3203407{col 43}{space 2}  .203832{col 54}{space 1}    1.57{col 63}{space 3}0.119{col 71}{space 4}-.0838659{col 84}{space 3} .7245472
{txt}{space 26}67  {c |}{col 31}{res}{space 2} .3265743{col 43}{space 2} .1319863{col 54}{space 1}    2.47{col 63}{space 3}0.015{col 71}{space 4} .0648405{col 84}{space 3}  .588308
{txt}{space 26}68  {c |}{col 31}{res}{space 2}  .315988{col 43}{space 2} .1489376{col 54}{space 1}    2.12{col 63}{space 3}0.036{col 71}{space 4} .0206392{col 84}{space 3} .6113368
{txt}{space 26}69  {c |}{col 31}{res}{space 2} .1942763{col 43}{space 2}  .114014{col 54}{space 1}    1.70{col 63}{space 3}0.091{col 71}{space 4}-.0318177{col 84}{space 3} .4203703
{txt}{space 26}70  {c |}{col 31}{res}{space 2}  .411581{col 43}{space 2} .1870099{col 54}{space 1}    2.20{col 63}{space 3}0.030{col 71}{space 4} .0407333{col 84}{space 3} .7824287
{txt}{space 26}71  {c |}{col 31}{res}{space 2} .1144767{col 43}{space 2} .1375705{col 54}{space 1}    0.83{col 63}{space 3}0.407{col 71}{space 4}-.1583308{col 84}{space 3} .3872842
{txt}{space 26}72  {c |}{col 31}{res}{space 2} .2745974{col 43}{space 2} .1118822{col 54}{space 1}    2.45{col 63}{space 3}0.016{col 71}{space 4} .0527308{col 84}{space 3} .4964641
{txt}{space 26}73  {c |}{col 31}{res}{space 2}   .49146{col 43}{space 2} .1689463{col 54}{space 1}    2.91{col 63}{space 3}0.004{col 71}{space 4} .1564332{col 84}{space 3} .8264868
{txt}{space 26}74  {c |}{col 31}{res}{space 2} .0962639{col 43}{space 2} .1080446{col 54}{space 1}    0.89{col 63}{space 3}0.375{col 71}{space 4}-.1179926{col 84}{space 3} .3105203
{txt}{space 26}75  {c |}{col 31}{res}{space 2} .1911289{col 43}{space 2} .1279844{col 54}{space 1}    1.49{col 63}{space 3}0.138{col 71}{space 4}-.0626689{col 84}{space 3} .4449268
{txt}{space 26}76  {c |}{col 31}{res}{space 2} .3345993{col 43}{space 2} .1536895{col 54}{space 1}    2.18{col 63}{space 3}0.032{col 71}{space 4} .0298272{col 84}{space 3} .6393714
{txt}{space 26}77  {c |}{col 31}{res}{space 2} .2648933{col 43}{space 2} .1458443{col 54}{space 1}    1.82{col 63}{space 3}0.072{col 71}{space 4}-.0243215{col 84}{space 3} .5541081
{txt}{space 26}78  {c |}{col 31}{res}{space 2} .2950275{col 43}{space 2} .0987851{col 54}{space 1}    2.99{col 63}{space 3}0.004{col 71}{space 4} .0991329{col 84}{space 3}  .490922
{txt}{space 26}79  {c |}{col 31}{res}{space 2}-.0134677{col 43}{space 2}  .016477{col 54}{space 1}   -0.82{col 63}{space 3}0.416{col 71}{space 4}-.0461422{col 84}{space 3} .0192068
{txt}{space 26}80  {c |}{col 31}{res}{space 2}  .434295{col 43}{space 2} .1730179{col 54}{space 1}    2.51{col 63}{space 3}0.014{col 71}{space 4} .0911939{col 84}{space 3} .7773961
{txt}{space 26}81  {c |}{col 31}{res}{space 2} .2190169{col 43}{space 2} .1778123{col 54}{space 1}    1.23{col 63}{space 3}0.221{col 71}{space 4}-.1335917{col 84}{space 3} .5716254
{txt}{space 26}82  {c |}{col 31}{res}{space 2} .3534107{col 43}{space 2} .1845837{col 54}{space 1}    1.91{col 63}{space 3}0.058{col 71}{space 4}-.0126257{col 84}{space 3} .7194471
{txt}{space 26}83  {c |}{col 31}{res}{space 2} .4291009{col 43}{space 2} .1454133{col 54}{space 1}    2.95{col 63}{space 3}0.004{col 71}{space 4} .1407409{col 84}{space 3} .7174609
{txt}{space 26}84  {c |}{col 31}{res}{space 2} .3314842{col 43}{space 2} .1846623{col 54}{space 1}    1.80{col 63}{space 3}0.076{col 71}{space 4}-.0347081{col 84}{space 3} .6976765
{txt}{space 26}85  {c |}{col 31}{res}{space 2} .4066459{col 43}{space 2} .1472483{col 54}{space 1}    2.76{col 63}{space 3}0.007{col 71}{space 4} .1146469{col 84}{space 3} .6986448
{txt}{space 26}86  {c |}{col 31}{res}{space 2} .4618178{col 43}{space 2} .1898559{col 54}{space 1}    2.43{col 63}{space 3}0.017{col 71}{space 4} .0853265{col 84}{space 3} .8383092
{txt}{space 26}87  {c |}{col 31}{res}{space 2} .4649132{col 43}{space 2} .1910974{col 54}{space 1}    2.43{col 63}{space 3}0.017{col 71}{space 4} .0859598{col 84}{space 3} .8438665
{txt}{space 26}88  {c |}{col 31}{res}{space 2} .2545288{col 43}{space 2} .1351366{col 54}{space 1}    1.88{col 63}{space 3}0.062{col 71}{space 4}-.0134521{col 84}{space 3} .5225097
{txt}{space 26}89  {c |}{col 31}{res}{space 2} .2984289{col 43}{space 2} .1459568{col 54}{space 1}    2.04{col 63}{space 3}0.043{col 71}{space 4} .0089912{col 84}{space 3} .5878667
{txt}{space 26}90  {c |}{col 31}{res}{space 2} .0790359{col 43}{space 2}  .108702{col 54}{space 1}    0.73{col 63}{space 3}0.469{col 71}{space 4}-.1365242{col 84}{space 3}  .294596
{txt}{space 26}91  {c |}{col 31}{res}{space 2} .1950981{col 43}{space 2} .1093899{col 54}{space 1}    1.78{col 63}{space 3}0.077{col 71}{space 4}-.0218261{col 84}{space 3} .4120223
{txt}{space 26}92  {c |}{col 31}{res}{space 2} .0806313{col 43}{space 2} .0446375{col 54}{space 1}    1.81{col 63}{space 3}0.074{col 71}{space 4}-.0078865{col 84}{space 3} .1691492
{txt}{space 26}93  {c |}{col 31}{res}{space 2} .4282975{col 43}{space 2} .1464597{col 54}{space 1}    2.92{col 63}{space 3}0.004{col 71}{space 4} .1378624{col 84}{space 3} .7187325
{txt}{space 26}94  {c |}{col 31}{res}{space 2} .4615874{col 43}{space 2} .1666943{col 54}{space 1}    2.77{col 63}{space 3}0.007{col 71}{space 4} .1310262{col 84}{space 3} .7921485
{txt}{space 26}95  {c |}{col 31}{res}{space 2} .2191553{col 43}{space 2} .1444089{col 54}{space 1}    1.52{col 63}{space 3}0.132{col 71}{space 4}-.0672128{col 84}{space 3} .5055235
{txt}{space 26}96  {c |}{col 31}{res}{space 2} .3406191{col 43}{space 2} .1543967{col 54}{space 1}    2.21{col 63}{space 3}0.030{col 71}{space 4} .0344447{col 84}{space 3} .6467936
{txt}{space 26}97  {c |}{col 31}{res}{space 2} .3972907{col 43}{space 2} .1484635{col 54}{space 1}    2.68{col 63}{space 3}0.009{col 71}{space 4}  .102882{col 84}{space 3} .6916994
{txt}{space 26}98  {c |}{col 31}{res}{space 2} .5585763{col 43}{space 2} .1841689{col 54}{space 1}    3.03{col 63}{space 3}0.003{col 71}{space 4} .1933626{col 84}{space 3} .9237901
{txt}{space 26}99  {c |}{col 31}{res}{space 2} .0902439{col 43}{space 2} .0915801{col 54}{space 1}    0.99{col 63}{space 3}0.327{col 71}{space 4}-.0913629{col 84}{space 3} .2718506
{txt}{space 25}100  {c |}{col 31}{res}{space 2} .2531328{col 43}{space 2} .1483244{col 54}{space 1}    1.71{col 63}{space 3}0.091{col 71}{space 4}-.0410001{col 84}{space 3} .5472656
{txt}{space 25}101  {c |}{col 31}{res}{space 2} .4055354{col 43}{space 2} .1342095{col 54}{space 1}    3.02{col 63}{space 3}0.003{col 71}{space 4}  .139393{col 84}{space 3} .6716779
{txt}{space 25}102  {c |}{col 31}{res}{space 2} .2557683{col 43}{space 2} .1533723{col 54}{space 1}    1.67{col 63}{space 3}0.098{col 71}{space 4}-.0483748{col 84}{space 3} .5599115
{txt}{space 25}103  {c |}{col 31}{res}{space 2} .0742748{col 43}{space 2}  .104961{col 54}{space 1}    0.71{col 63}{space 3}0.481{col 71}{space 4}-.1338669{col 84}{space 3} .2824164
{txt}{space 25}104  {c |}{col 31}{res}{space 2}-.1001571{col 43}{space 2} .0749685{col 54}{space 1}   -1.34{col 63}{space 3}0.184{col 71}{space 4}-.2488223{col 84}{space 3} .0485082
{txt}{space 25}105  {c |}{col 31}{res}{space 2} .3353586{col 43}{space 2} .1527655{col 54}{space 1}    2.20{col 63}{space 3}0.030{col 71}{space 4} .0324188{col 84}{space 3} .6382984
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}2011  {c |}{col 31}{res}{space 2}-.0041181{col 43}{space 2} .0032302{col 54}{space 1}   -1.27{col 63}{space 3}0.205{col 71}{space 4}-.0105238{col 84}{space 3} .0022876
{txt}{space 24}2012  {c |}{col 31}{res}{space 2} .0001421{col 43}{space 2} .0044937{col 54}{space 1}    0.03{col 63}{space 3}0.975{col 71}{space 4} -.008769{col 84}{space 3} .0090532
{txt}{space 24}2013  {c |}{col 31}{res}{space 2}-.0010345{col 43}{space 2} .0049842{col 54}{space 1}   -0.21{col 63}{space 3}0.836{col 71}{space 4}-.0109183{col 84}{space 3} .0088493
{txt}{space 24}2014  {c |}{col 31}{res}{space 2}-.0070407{col 43}{space 2} .0070398{col 54}{space 1}   -1.00{col 63}{space 3}0.320{col 71}{space 4}-.0210009{col 84}{space 3} .0069195
{txt}{space 24}2015  {c |}{col 31}{res}{space 2}-.0145928{col 43}{space 2} .0085983{col 54}{space 1}   -1.70{col 63}{space 3}0.093{col 71}{space 4}-.0316436{col 84}{space 3}  .002458
{txt}{space 24}2016  {c |}{col 31}{res}{space 2}-.0177912{col 43}{space 2} .0074095{col 54}{space 1}   -2.40{col 63}{space 3}0.018{col 71}{space 4}-.0324845{col 84}{space 3} -.003098
{txt}{space 24}2017  {c |}{col 31}{res}{space 2}-.0036555{col 43}{space 2} .0095597{col 54}{space 1}   -0.38{col 63}{space 3}0.703{col 71}{space 4}-.0226127{col 84}{space 3} .0153017
{txt}{space 24}2018  {c |}{col 31}{res}{space 2}-.0327448{col 43}{space 2} .0073556{col 54}{space 1}   -4.45{col 63}{space 3}0.000{col 71}{space 4}-.0473312{col 84}{space 3}-.0181585
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-.0710326{col 43}{space 2} .0084319{col 54}{space 1}   -8.42{col 63}{space 3}0.000{col 71}{space 4}-.0877533{col 84}{space 3}-.0543119
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2}-.1246093{col 43}{space 2}  .415681{col 54}{space 1}   -0.30{col 63}{space 3}0.765{col 71}{space 4}-.9489202{col 84}{space 3} .6997017
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891389{col 50}    18{col 58}  3782815{col 69}  3783044
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1524577{col 26}{space 2} .0417215{col 37}{space 1}    3.65{col 46}{space 3}0.000{col 54}{space 4} .0697225{col 67}{space 3}  .235193
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0001655{col 26}{space 2} .0193692{col 37}{space 1}   -0.01{col 46}{space 3}0.993{col 54}{space 4}-.0385754{col 67}{space 3} .0382443
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
.    
. *** MODEL 2: CONDITIONAL RESPONSES BY RACE/ETHNICITY -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS  WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. 
. regress  lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority   ln_ratio_min_tot_nmin_tot    gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(17, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0403
                                                {txt}Root MSE          =    {res} .51455

{txt}{ralign 99:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 34}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 35}{c |}{col 47}    Robust
{col 1}              lndiversity2zeroadj{col 35}{c |} Coefficient{col 47}  std. err.{col 59}      t{col 67}   P>|t|{col 75}     [95% con{col 88}f. interval]
{hline 34}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}ln_ratio_mnmsup_mnmsub {c |}{col 35}{res}{space 2}  .052221{col 47}{space 2} .0338126{col 58}{space 1}    1.54{col 67}{space 3}0.126{col 75}{space 4}-.0148307{col 88}{space 3} .1192727
{txt}{space 23}1.minority {c |}{col 35}{res}{space 2}-.0781252{col 47}{space 2}  .005869{col 58}{space 1}  -13.31{col 67}{space 3}0.000{col 75}{space 4}-.0897637{col 88}{space 3}-.0664868
{txt}{space 33} {c |}
minority#c.ln_ratio_mnmsup_mnmsub {c |}
{space 31}1  {c |}{col 35}{res}{space 2} .0474209{col 47}{space 2} .0164652{col 58}{space 1}    2.88{col 67}{space 3}0.005{col 75}{space 4} .0147698{col 88}{space 3} .0800721
{txt}{space 33} {c |}
{space 8}ln_ratio_min_tot_nmin_tot {c |}{col 35}{res}{space 2} .0537025{col 47}{space 2} .0449943{col 58}{space 1}    1.19{col 67}{space 3}0.235{col 75}{space 4}-.0355228{col 88}{space 3} .1429278
{txt}{space 27}gender {c |}{col 35}{res}{space 2}-.0395518{col 47}{space 2} .0041555{col 58}{space 1}   -9.52{col 67}{space 3}0.000{col 75}{space 4}-.0477923{col 88}{space 3}-.0313112
{txt}{space 23}supervisor {c |}{col 35}{res}{space 2} .1271897{col 47}{space 2} .0074093{col 58}{space 1}   17.17{col 67}{space 3}0.000{col 75}{space 4} .1124968{col 88}{space 3} .1418827
{txt}{space 17}topoffminority_2 {c |}{col 35}{res}{space 2} .0075476{col 47}{space 2} .0059151{col 58}{space 1}    1.28{col 67}{space 3}0.205{col 75}{space 4}-.0041823{col 88}{space 3} .0192775
{txt}{space 13}lntotworkforce_count {c |}{col 35}{res}{space 2} .0652955{col 47}{space 2} .0401998{col 58}{space 1}    1.62{col 67}{space 3}0.107{col 75}{space 4}-.0144222{col 88}{space 3} .1450132
{txt}{space 5}ln_professionals_total_ratio {c |}{col 35}{res}{space 2} .0219033{col 47}{space 2} .0503137{col 58}{space 1}    0.44{col 67}{space 3}0.664{col 75}{space 4}-.0778707{col 88}{space 3} .1216772
{txt}{space 33} {c |}
{space 25}agencyid {c |}
{space 31}2  {c |}{col 35}{res}{space 2} .2131513{col 47}{space 2} .1222535{col 58}{space 1}    1.74{col 67}{space 3}0.084{col 75}{space 4} -.029282{col 88}{space 3} .4555846
{txt}{space 31}3  {c |}{col 35}{res}{space 2} .0345513{col 47}{space 2} .0540178{col 58}{space 1}    0.64{col 67}{space 3}0.524{col 75}{space 4}-.0725679{col 88}{space 3} .1416706
{txt}{space 31}4  {c |}{col 35}{res}{space 2} .2843101{col 47}{space 2} .1640039{col 58}{space 1}    1.73{col 67}{space 3}0.086{col 75}{space 4}-.0409158{col 88}{space 3}  .609536
{txt}{space 31}5  {c |}{col 35}{res}{space 2} .1690709{col 47}{space 2} .1271602{col 58}{space 1}    1.33{col 67}{space 3}0.187{col 75}{space 4}-.0830925{col 88}{space 3} .4212343
{txt}{space 31}6  {c |}{col 35}{res}{space 2}  .174625{col 47}{space 2} .1183515{col 58}{space 1}    1.48{col 67}{space 3}0.143{col 75}{space 4}-.0600705{col 88}{space 3} .4093205
{txt}{space 31}7  {c |}{col 35}{res}{space 2} .2457407{col 47}{space 2} .2169604{col 58}{space 1}    1.13{col 67}{space 3}0.260{col 75}{space 4}-.1844999{col 88}{space 3} .6759813
{txt}{space 31}8  {c |}{col 35}{res}{space 2} .2342343{col 47}{space 2} .1623216{col 58}{space 1}    1.44{col 67}{space 3}0.152{col 75}{space 4}-.0876556{col 88}{space 3} .5561242
{txt}{space 31}9  {c |}{col 35}{res}{space 2}-.0557047{col 47}{space 2} .0230108{col 58}{space 1}   -2.42{col 67}{space 3}0.017{col 75}{space 4}-.1013359{col 88}{space 3}-.0100735
{txt}{space 30}10  {c |}{col 35}{res}{space 2} .1931665{col 47}{space 2} .2310979{col 58}{space 1}    0.84{col 67}{space 3}0.405{col 75}{space 4}-.2651092{col 88}{space 3} .6514423
{txt}{space 30}11  {c |}{col 35}{res}{space 2}  .161717{col 47}{space 2} .1046472{col 58}{space 1}    1.55{col 67}{space 3}0.125{col 75}{space 4}-.0458024{col 88}{space 3} .3692363
{txt}{space 30}12  {c |}{col 35}{res}{space 2}  .317924{col 47}{space 2} .2145972{col 58}{space 1}    1.48{col 67}{space 3}0.141{col 75}{space 4}-.1076303{col 88}{space 3} .7434783
{txt}{space 30}13  {c |}{col 35}{res}{space 2}   .31492{col 47}{space 2} .1624066{col 58}{space 1}    1.94{col 67}{space 3}0.055{col 75}{space 4}-.0071384{col 88}{space 3} .6369785
{txt}{space 30}14  {c |}{col 35}{res}{space 2} .1578857{col 47}{space 2} .1099156{col 58}{space 1}    1.44{col 67}{space 3}0.154{col 75}{space 4}-.0600811{col 88}{space 3} .3758524
{txt}{space 30}15  {c |}{col 35}{res}{space 2} .2347055{col 47}{space 2}  .154184{col 58}{space 1}    1.52{col 67}{space 3}0.131{col 75}{space 4}-.0710473{col 88}{space 3} .5404582
{txt}{space 30}16  {c |}{col 35}{res}{space 2} .2037385{col 47}{space 2} .2875001{col 58}{space 1}    0.71{col 67}{space 3}0.480{col 75}{space 4} -.366385{col 88}{space 3}  .773862
{txt}{space 30}17  {c |}{col 35}{res}{space 2} .0464887{col 47}{space 2} .1879458{col 58}{space 1}    0.25{col 67}{space 3}0.805{col 75}{space 4}-.3262149{col 88}{space 3} .4191923
{txt}{space 30}18  {c |}{col 35}{res}{space 2} .3098273{col 47}{space 2} .1690716{col 58}{space 1}    1.83{col 67}{space 3}0.070{col 75}{space 4}-.0254481{col 88}{space 3} .6451027
{txt}{space 30}19  {c |}{col 35}{res}{space 2} .1800803{col 47}{space 2} .1143435{col 58}{space 1}    1.57{col 67}{space 3}0.118{col 75}{space 4}-.0466672{col 88}{space 3} .4068277
{txt}{space 30}20  {c |}{col 35}{res}{space 2} .0603144{col 47}{space 2} .1201425{col 58}{space 1}    0.50{col 67}{space 3}0.617{col 75}{space 4}-.1779326{col 88}{space 3} .2985615
{txt}{space 30}21  {c |}{col 35}{res}{space 2} .2128748{col 47}{space 2} .1095464{col 58}{space 1}    1.94{col 67}{space 3}0.055{col 75}{space 4}-.0043599{col 88}{space 3} .4301095
{txt}{space 30}22  {c |}{col 35}{res}{space 2}  .148973{col 47}{space 2} .1735369{col 58}{space 1}    0.86{col 67}{space 3}0.393{col 75}{space 4}-.1951573{col 88}{space 3} .4931032
{txt}{space 30}23  {c |}{col 35}{res}{space 2}-.1032951{col 47}{space 2} .0875464{col 58}{space 1}   -1.18{col 67}{space 3}0.241{col 75}{space 4}-.2769028{col 88}{space 3} .0703126
{txt}{space 30}24  {c |}{col 35}{res}{space 2} .2487472{col 47}{space 2} .1221549{col 58}{space 1}    2.04{col 67}{space 3}0.044{col 75}{space 4} .0065094{col 88}{space 3}  .490985
{txt}{space 30}25  {c |}{col 35}{res}{space 2} .1902944{col 47}{space 2} .1487222{col 58}{space 1}    1.28{col 67}{space 3}0.204{col 75}{space 4}-.1046273{col 88}{space 3}  .485216
{txt}{space 30}26  {c |}{col 35}{res}{space 2}  .052674{col 47}{space 2} .1315902{col 58}{space 1}    0.40{col 67}{space 3}0.690{col 75}{space 4}-.2082742{col 88}{space 3} .3136222
{txt}{space 30}27  {c |}{col 35}{res}{space 2} .3590825{col 47}{space 2} .1969099{col 58}{space 1}    1.82{col 67}{space 3}0.071{col 75}{space 4}-.0313972{col 88}{space 3} .7495622
{txt}{space 30}28  {c |}{col 35}{res}{space 2} -.048736{col 47}{space 2}  .111451{col 58}{space 1}   -0.44{col 67}{space 3}0.663{col 75}{space 4}-.2697475{col 88}{space 3} .1722755
{txt}{space 30}29  {c |}{col 35}{res}{space 2}  .081671{col 47}{space 2} .1874795{col 58}{space 1}    0.44{col 67}{space 3}0.664{col 75}{space 4} -.290108{col 88}{space 3} .4534499
{txt}{space 30}30  {c |}{col 35}{res}{space 2} .1614484{col 47}{space 2} .1734271{col 58}{space 1}    0.93{col 67}{space 3}0.354{col 75}{space 4}-.1824641{col 88}{space 3} .5053608
{txt}{space 30}31  {c |}{col 35}{res}{space 2}-.0190388{col 47}{space 2} .1794092{col 58}{space 1}   -0.11{col 67}{space 3}0.916{col 75}{space 4}-.3748139{col 88}{space 3} .3367364
{txt}{space 30}32  {c |}{col 35}{res}{space 2} .2072473{col 47}{space 2} .1421993{col 58}{space 1}    1.46{col 67}{space 3}0.148{col 75}{space 4}-.0747393{col 88}{space 3} .4892338
{txt}{space 30}33  {c |}{col 35}{res}{space 2} .1205354{col 47}{space 2} .0894519{col 58}{space 1}    1.35{col 67}{space 3}0.181{col 75}{space 4} -.056851{col 88}{space 3} .2979218
{txt}{space 30}34  {c |}{col 35}{res}{space 2}-.1469366{col 47}{space 2}  .226958{col 58}{space 1}   -0.65{col 67}{space 3}0.519{col 75}{space 4}-.5970029{col 88}{space 3} .3031297
{txt}{space 30}35  {c |}{col 35}{res}{space 2} .1413569{col 47}{space 2} .1022553{col 58}{space 1}    1.38{col 67}{space 3}0.170{col 75}{space 4}-.0614191{col 88}{space 3} .3441329
{txt}{space 30}36  {c |}{col 35}{res}{space 2} .2141284{col 47}{space 2} .1349089{col 58}{space 1}    1.59{col 67}{space 3}0.116{col 75}{space 4} -.053401{col 88}{space 3} .4816579
{txt}{space 30}37  {c |}{col 35}{res}{space 2} .1983311{col 47}{space 2} .1148195{col 58}{space 1}    1.73{col 67}{space 3}0.087{col 75}{space 4}-.0293604{col 88}{space 3} .4260225
{txt}{space 30}38  {c |}{col 35}{res}{space 2} .3113679{col 47}{space 2} .1959253{col 58}{space 1}    1.59{col 67}{space 3}0.115{col 75}{space 4}-.0771593{col 88}{space 3} .6998951
{txt}{space 30}39  {c |}{col 35}{res}{space 2} .2169638{col 47}{space 2} .1176442{col 58}{space 1}    1.84{col 67}{space 3}0.068{col 75}{space 4}-.0163291{col 88}{space 3} .4502567
{txt}{space 30}40  {c |}{col 35}{res}{space 2} .0444153{col 47}{space 2} .0781409{col 58}{space 1}    0.57{col 67}{space 3}0.571{col 75}{space 4}-.1105411{col 88}{space 3} .1993717
{txt}{space 30}41  {c |}{col 35}{res}{space 2} .1842315{col 47}{space 2} .1715991{col 58}{space 1}    1.07{col 67}{space 3}0.285{col 75}{space 4} -.156056{col 88}{space 3} .5245191
{txt}{space 30}42  {c |}{col 35}{res}{space 2} .2205798{col 47}{space 2} .1607249{col 58}{space 1}    1.37{col 67}{space 3}0.173{col 75}{space 4}-.0981436{col 88}{space 3} .5393032
{txt}{space 30}43  {c |}{col 35}{res}{space 2} .0069879{col 47}{space 2} .0738389{col 58}{space 1}    0.09{col 67}{space 3}0.925{col 75}{space 4}-.1394375{col 88}{space 3} .1534132
{txt}{space 30}44  {c |}{col 35}{res}{space 2} .2589764{col 47}{space 2} .1371872{col 58}{space 1}    1.89{col 67}{space 3}0.062{col 75}{space 4}-.0130708{col 88}{space 3} .5310237
{txt}{space 30}45  {c |}{col 35}{res}{space 2} .2218591{col 47}{space 2} .1203212{col 58}{space 1}    1.84{col 67}{space 3}0.068{col 75}{space 4}-.0167424{col 88}{space 3} .4604606
{txt}{space 30}46  {c |}{col 35}{res}{space 2} .1302168{col 47}{space 2} .2121986{col 58}{space 1}    0.61{col 67}{space 3}0.541{col 75}{space 4}-.2905809{col 88}{space 3} .5510146
{txt}{space 30}47  {c |}{col 35}{res}{space 2} .1544162{col 47}{space 2} .0925154{col 58}{space 1}    1.67{col 67}{space 3}0.098{col 75}{space 4}-.0290453{col 88}{space 3} .3378776
{txt}{space 30}48  {c |}{col 35}{res}{space 2} .2402855{col 47}{space 2} .1889356{col 58}{space 1}    1.27{col 67}{space 3}0.206{col 75}{space 4}-.1343809{col 88}{space 3}  .614952
{txt}{space 30}49  {c |}{col 35}{res}{space 2} .3349208{col 47}{space 2} .2040951{col 58}{space 1}    1.64{col 67}{space 3}0.104{col 75}{space 4}-.0698074{col 88}{space 3} .7396489
{txt}{space 30}50  {c |}{col 35}{res}{space 2} .3465209{col 47}{space 2} .1844124{col 58}{space 1}    1.88{col 67}{space 3}0.063{col 75}{space 4}-.0191758{col 88}{space 3} .7122177
{txt}{space 30}51  {c |}{col 35}{res}{space 2} .3402451{col 47}{space 2} .2315446{col 58}{space 1}    1.47{col 67}{space 3}0.145{col 75}{space 4}-.1189165{col 88}{space 3} .7994068
{txt}{space 30}52  {c |}{col 35}{res}{space 2} .2370264{col 47}{space 2} .2312178{col 58}{space 1}    1.03{col 67}{space 3}0.308{col 75}{space 4}-.2214873{col 88}{space 3}   .69554
{txt}{space 30}53  {c |}{col 35}{res}{space 2} .2725105{col 47}{space 2} .1662351{col 58}{space 1}    1.64{col 67}{space 3}0.104{col 75}{space 4}  -.05714{col 88}{space 3}  .602161
{txt}{space 30}54  {c |}{col 35}{res}{space 2} .2929537{col 47}{space 2} .1840284{col 58}{space 1}    1.59{col 67}{space 3}0.114{col 75}{space 4}-.0719816{col 88}{space 3}  .657889
{txt}{space 30}55  {c |}{col 35}{res}{space 2} .4179899{col 47}{space 2} .2352937{col 58}{space 1}    1.78{col 67}{space 3}0.079{col 75}{space 4}-.0486063{col 88}{space 3} .8845861
{txt}{space 30}56  {c |}{col 35}{res}{space 2} .2494621{col 47}{space 2} .2411149{col 58}{space 1}    1.03{col 67}{space 3}0.303{col 75}{space 4}-.2286779{col 88}{space 3}  .727602
{txt}{space 30}57  {c |}{col 35}{res}{space 2}  .318018{col 47}{space 2} .3042717{col 58}{space 1}    1.05{col 67}{space 3}0.298{col 75}{space 4}-.2853641{col 88}{space 3} .9214002
{txt}{space 30}58  {c |}{col 35}{res}{space 2} .1991536{col 47}{space 2} .1742152{col 58}{space 1}    1.14{col 67}{space 3}0.256{col 75}{space 4}-.1463218{col 88}{space 3} .5446289
{txt}{space 30}59  {c |}{col 35}{res}{space 2} .1972223{col 47}{space 2} .2090772{col 58}{space 1}    0.94{col 67}{space 3}0.348{col 75}{space 4}-.2173856{col 88}{space 3} .6118303
{txt}{space 30}60  {c |}{col 35}{res}{space 2} .1455243{col 47}{space 2} .1034617{col 58}{space 1}    1.41{col 67}{space 3}0.163{col 75}{space 4}-.0596442{col 88}{space 3} .3506927
{txt}{space 30}61  {c |}{col 35}{res}{space 2} .1371671{col 47}{space 2}  .110421{col 58}{space 1}    1.24{col 67}{space 3}0.217{col 75}{space 4}-.0818019{col 88}{space 3}  .356136
{txt}{space 30}62  {c |}{col 35}{res}{space 2} .3212165{col 47}{space 2} .2065297{col 58}{space 1}    1.56{col 67}{space 3}0.123{col 75}{space 4}-.0883397{col 88}{space 3} .7307727
{txt}{space 30}63  {c |}{col 35}{res}{space 2} .3913892{col 47}{space 2} .2009726{col 58}{space 1}    1.95{col 67}{space 3}0.054{col 75}{space 4}-.0071469{col 88}{space 3} .7899254
{txt}{space 30}64  {c |}{col 35}{res}{space 2} .4025031{col 47}{space 2} .2108095{col 58}{space 1}    1.91{col 67}{space 3}0.059{col 75}{space 4}-.0155401{col 88}{space 3} .8205462
{txt}{space 30}65  {c |}{col 35}{res}{space 2}  .213348{col 47}{space 2} .1212193{col 58}{space 1}    1.76{col 67}{space 3}0.081{col 75}{space 4}-.0270345{col 88}{space 3} .4537305
{txt}{space 30}66  {c |}{col 35}{res}{space 2} .1927226{col 47}{space 2} .2235197{col 58}{space 1}    0.86{col 67}{space 3}0.391{col 75}{space 4}-.2505254{col 88}{space 3} .6359706
{txt}{space 30}67  {c |}{col 35}{res}{space 2} .2237339{col 47}{space 2} .1367459{col 58}{space 1}    1.64{col 67}{space 3}0.105{col 75}{space 4}-.0474383{col 88}{space 3} .4949062
{txt}{space 30}68  {c |}{col 35}{res}{space 2} .2814959{col 47}{space 2} .1524426{col 58}{space 1}    1.85{col 67}{space 3}0.068{col 75}{space 4}-.0208036{col 88}{space 3} .5837953
{txt}{space 30}69  {c |}{col 35}{res}{space 2} .1423686{col 47}{space 2} .1226743{col 58}{space 1}    1.16{col 67}{space 3}0.248{col 75}{space 4} -.100899{col 88}{space 3} .3856363
{txt}{space 30}70  {c |}{col 35}{res}{space 2} .3501453{col 47}{space 2} .2106972{col 58}{space 1}    1.66{col 67}{space 3}0.100{col 75}{space 4}-.0676752{col 88}{space 3} .7679658
{txt}{space 30}71  {c |}{col 35}{res}{space 2}-.1070453{col 47}{space 2} .1816589{col 58}{space 1}   -0.59{col 67}{space 3}0.557{col 75}{space 4}-.4672816{col 88}{space 3} .2531911
{txt}{space 30}72  {c |}{col 35}{res}{space 2}  .201511{col 47}{space 2} .1184194{col 58}{space 1}    1.70{col 67}{space 3}0.092{col 75}{space 4} -.033319{col 88}{space 3} .4363411
{txt}{space 30}73  {c |}{col 35}{res}{space 2}  .426842{col 47}{space 2} .1920147{col 58}{space 1}    2.22{col 67}{space 3}0.028{col 75}{space 4} .0460696{col 88}{space 3} .8076143
{txt}{space 30}74  {c |}{col 35}{res}{space 2}  .152328{col 47}{space 2} .1023165{col 58}{space 1}    1.49{col 67}{space 3}0.140{col 75}{space 4}-.0505695{col 88}{space 3} .3552256
{txt}{space 30}75  {c |}{col 35}{res}{space 2} .0698803{col 47}{space 2} .1503469{col 58}{space 1}    0.46{col 67}{space 3}0.643{col 75}{space 4}-.2282632{col 88}{space 3} .3680239
{txt}{space 30}76  {c |}{col 35}{res}{space 2} .2959861{col 47}{space 2} .1724877{col 58}{space 1}    1.72{col 67}{space 3}0.089{col 75}{space 4}-.0460634{col 88}{space 3} .6380356
{txt}{space 30}77  {c |}{col 35}{res}{space 2} .2231094{col 47}{space 2} .1710917{col 58}{space 1}    1.30{col 67}{space 3}0.195{col 75}{space 4}-.1161719{col 88}{space 3} .5623907
{txt}{space 30}78  {c |}{col 35}{res}{space 2}  .269932{col 47}{space 2} .1092915{col 58}{space 1}    2.47{col 67}{space 3}0.015{col 75}{space 4} .0532029{col 88}{space 3} .4866611
{txt}{space 30}79  {c |}{col 35}{res}{space 2}-.0168125{col 47}{space 2} .0254716{col 58}{space 1}   -0.66{col 67}{space 3}0.511{col 75}{space 4}-.0673235{col 88}{space 3} .0336986
{txt}{space 30}80  {c |}{col 35}{res}{space 2} .4360701{col 47}{space 2} .2175563{col 58}{space 1}    2.00{col 67}{space 3}0.048{col 75}{space 4} .0046479{col 88}{space 3} .8674924
{txt}{space 30}81  {c |}{col 35}{res}{space 2} .1657869{col 47}{space 2} .2381287{col 58}{space 1}    0.70{col 67}{space 3}0.488{col 75}{space 4}-.3064312{col 88}{space 3}  .638005
{txt}{space 30}82  {c |}{col 35}{res}{space 2} .2361031{col 47}{space 2}  .204008{col 58}{space 1}    1.16{col 67}{space 3}0.250{col 75}{space 4}-.1684525{col 88}{space 3} .6406586
{txt}{space 30}83  {c |}{col 35}{res}{space 2} .3458474{col 47}{space 2} .1688843{col 58}{space 1}    2.05{col 67}{space 3}0.043{col 75}{space 4} .0109435{col 88}{space 3} .6807512
{txt}{space 30}84  {c |}{col 35}{res}{space 2} .2872109{col 47}{space 2} .2071026{col 58}{space 1}    1.39{col 67}{space 3}0.168{col 75}{space 4}-.1234813{col 88}{space 3} .6979031
{txt}{space 30}85  {c |}{col 35}{res}{space 2} .3062624{col 47}{space 2} .1612061{col 58}{space 1}    1.90{col 67}{space 3}0.060{col 75}{space 4}-.0134154{col 88}{space 3} .6259403
{txt}{space 30}86  {c |}{col 35}{res}{space 2} .3283386{col 47}{space 2} .2400205{col 58}{space 1}    1.37{col 67}{space 3}0.174{col 75}{space 4} -.147631{col 88}{space 3} .8043083
{txt}{space 30}87  {c |}{col 35}{res}{space 2} .3833226{col 47}{space 2} .2400027{col 58}{space 1}    1.60{col 67}{space 3}0.113{col 75}{space 4}-.0926116{col 88}{space 3} .8592569
{txt}{space 30}88  {c |}{col 35}{res}{space 2}  .171122{col 47}{space 2} .1688751{col 58}{space 1}    1.01{col 67}{space 3}0.313{col 75}{space 4}-.1637638{col 88}{space 3} .5060077
{txt}{space 30}89  {c |}{col 35}{res}{space 2} .2303813{col 47}{space 2} .1641508{col 58}{space 1}    1.40{col 67}{space 3}0.163{col 75}{space 4}-.0951359{col 88}{space 3} .5558985
{txt}{space 30}90  {c |}{col 35}{res}{space 2} .0213091{col 47}{space 2} .0839071{col 58}{space 1}    0.25{col 67}{space 3}0.800{col 75}{space 4}-.1450819{col 88}{space 3}    .1877
{txt}{space 30}91  {c |}{col 35}{res}{space 2} .1426334{col 47}{space 2} .1180526{col 58}{space 1}    1.21{col 67}{space 3}0.230{col 75}{space 4}-.0914694{col 88}{space 3} .3767362
{txt}{space 30}92  {c |}{col 35}{res}{space 2} .0818988{col 47}{space 2}   .05969{col 58}{space 1}    1.37{col 67}{space 3}0.173{col 75}{space 4}-.0364688{col 88}{space 3} .2002664
{txt}{space 30}93  {c |}{col 35}{res}{space 2} .3557668{col 47}{space 2} .1728199{col 58}{space 1}    2.06{col 67}{space 3}0.042{col 75}{space 4} .0130585{col 88}{space 3} .6984751
{txt}{space 30}94  {c |}{col 35}{res}{space 2} .4512523{col 47}{space 2} .2120741{col 58}{space 1}    2.13{col 67}{space 3}0.036{col 75}{space 4} .0307013{col 88}{space 3} .8718033
{txt}{space 30}95  {c |}{col 35}{res}{space 2} .1714416{col 47}{space 2} .2080537{col 58}{space 1}    0.82{col 67}{space 3}0.412{col 75}{space 4}-.2411367{col 88}{space 3}   .58402
{txt}{space 30}96  {c |}{col 35}{res}{space 2} .2966197{col 47}{space 2} .1881543{col 58}{space 1}    1.58{col 67}{space 3}0.118{col 75}{space 4}-.0764973{col 88}{space 3} .6697367
{txt}{space 30}97  {c |}{col 35}{res}{space 2} .3340263{col 47}{space 2} .1537906{col 58}{space 1}    2.17{col 67}{space 3}0.032{col 75}{space 4} .0290537{col 88}{space 3}  .638999
{txt}{space 30}98  {c |}{col 35}{res}{space 2} .4441757{col 47}{space 2} .2213763{col 58}{space 1}    2.01{col 67}{space 3}0.047{col 75}{space 4} .0051781{col 88}{space 3} .8831733
{txt}{space 30}99  {c |}{col 35}{res}{space 2} .0449787{col 47}{space 2} .0560085{col 58}{space 1}    0.80{col 67}{space 3}0.424{col 75}{space 4}-.0660882{col 88}{space 3} .1560456
{txt}{space 29}100  {c |}{col 35}{res}{space 2} .2112629{col 47}{space 2} .2102332{col 58}{space 1}    1.00{col 67}{space 3}0.317{col 75}{space 4}-.2056375{col 88}{space 3} .6281633
{txt}{space 29}101  {c |}{col 35}{res}{space 2} .3694827{col 47}{space 2} .1665632{col 58}{space 1}    2.22{col 67}{space 3}0.029{col 75}{space 4} .0391817{col 88}{space 3} .6997837
{txt}{space 29}102  {c |}{col 35}{res}{space 2} .2793875{col 47}{space 2} .2136669{col 58}{space 1}    1.31{col 67}{space 3}0.194{col 75}{space 4}-.1443218{col 88}{space 3} .7030969
{txt}{space 29}103  {c |}{col 35}{res}{space 2} .0815993{col 47}{space 2} .1172278{col 58}{space 1}    0.70{col 67}{space 3}0.488{col 75}{space 4}-.1508678{col 88}{space 3} .3140663
{txt}{space 29}104  {c |}{col 35}{res}{space 2}-.1587472{col 47}{space 2} .0605087{col 58}{space 1}   -2.62{col 67}{space 3}0.010{col 75}{space 4}-.2787383{col 88}{space 3}-.0387562
{txt}{space 29}105  {c |}{col 35}{res}{space 2} .2298147{col 47}{space 2} .1992811{col 58}{space 1}    1.15{col 67}{space 3}0.251{col 75}{space 4}-.1653671{col 88}{space 3} .6249965
{txt}{space 33} {c |}
{space 29}year {c |}
{space 28}2011  {c |}{col 35}{res}{space 2}-.0023419{col 47}{space 2} .0037595{col 58}{space 1}   -0.62{col 67}{space 3}0.535{col 75}{space 4} -.009797{col 88}{space 3} .0051132
{txt}{space 28}2012  {c |}{col 35}{res}{space 2} .0047115{col 47}{space 2} .0045072{col 58}{space 1}    1.05{col 67}{space 3}0.298{col 75}{space 4}-.0042265{col 88}{space 3} .0136495
{txt}{space 28}2013  {c |}{col 35}{res}{space 2} .0027375{col 47}{space 2} .0056016{col 58}{space 1}    0.49{col 67}{space 3}0.626{col 75}{space 4}-.0083706{col 88}{space 3} .0138456
{txt}{space 28}2014  {c |}{col 35}{res}{space 2}-.0022981{col 47}{space 2} .0065833{col 58}{space 1}   -0.35{col 67}{space 3}0.728{col 75}{space 4}-.0153531{col 88}{space 3} .0107568
{txt}{space 28}2015  {c |}{col 35}{res}{space 2}-.0101638{col 47}{space 2} .0080039{col 58}{space 1}   -1.27{col 67}{space 3}0.207{col 75}{space 4}-.0260357{col 88}{space 3} .0057081
{txt}{space 28}2016  {c |}{col 35}{res}{space 2}-.0130918{col 47}{space 2} .0079779{col 58}{space 1}   -1.64{col 67}{space 3}0.104{col 75}{space 4}-.0289122{col 88}{space 3} .0027286
{txt}{space 28}2017  {c |}{col 35}{res}{space 2}-.0028808{col 47}{space 2} .0117751{col 58}{space 1}   -0.24{col 67}{space 3}0.807{col 75}{space 4}-.0262312{col 88}{space 3} .0204696
{txt}{space 28}2018  {c |}{col 35}{res}{space 2}-.0292505{col 47}{space 2}  .010709{col 58}{space 1}   -2.73{col 67}{space 3}0.007{col 75}{space 4}-.0504869{col 88}{space 3}-.0080141
{txt}{space 28}2019  {c |}{col 35}{res}{space 2}-.0684553{col 47}{space 2} .0121103{col 58}{space 1}   -5.65{col 67}{space 3}0.000{col 75}{space 4}-.0924704{col 88}{space 3}-.0444401
{txt}{space 33} {c |}
{space 28}_cons {c |}{col 35}{res}{space 2} .0399902{col 47}{space 2} .5060156{col 58}{space 1}    0.08{col 67}{space 3}0.937{col 75}{space 4}-.9634578{col 88}{space 3} 1.043438
{txt}{hline 34}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891482{col 50}    18{col 58}  3783000{col 69}  3783229
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .052221{col 26}{space 2} .0338126{col 37}{space 1}    1.54{col 46}{space 3}0.126{col 54}{space 4}-.0148307{col 67}{space 3} .1192727
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0474209{col 26}{space 2} .0164652{col 37}{space 1}    2.88{col 46}{space 3}0.005{col 54}{space 4} .0147698{col 67}{space 3} .0800721
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. *
. *
. 
.   
. *** MODEL 3: CONDITIONAL RESPONSES BY MINORITY WOMEN VERSUS WHITE WOMEN [BASELINE CATEGORY: MEN RESPONDENTS] -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. 
. regress lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.women_het    ln_ratio_fem_tot_men_tot   minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(19, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0407
                                                {txt}Root MSE          =    {res} .51446

{txt}{ralign 98:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 33}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 34}{c |}{col 46}    Robust
{col 1}             lndiversity2zeroadj{col 34}{c |} Coefficient{col 46}  std. err.{col 58}      t{col 66}   P>|t|{col 74}     [95% con{col 87}f. interval]
{hline 33}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}ln_ratio_fmsup_fmsub {c |}{col 34}{res}{space 2} .1514916{col 46}{space 2} .0418288{col 57}{space 1}    3.62{col 66}{space 3}0.000{col 74}{space 4} .0685435{col 87}{space 3} .2344396
{txt}{space 32} {c |}
{space 23}women_het {c |}
{space 30}1  {c |}{col 34}{res}{space 2}-.0278468{col 46}{space 2} .0079202{col 57}{space 1}   -3.52{col 66}{space 3}0.001{col 74}{space 4}-.0435528{col 87}{space 3}-.0121407
{txt}{space 30}2  {c |}{col 34}{res}{space 2} -.059556{col 46}{space 2} .0072371{col 57}{space 1}   -8.23{col 66}{space 3}0.000{col 74}{space 4}-.0739076{col 87}{space 3}-.0452045
{txt}{space 32} {c |}
women_het#c.ln_ratio_fmsup_fmsub {c |}
{space 30}1  {c |}{col 34}{res}{space 2}-.0032998{col 46}{space 2} .0210083{col 57}{space 1}   -0.16{col 66}{space 3}0.875{col 74}{space 4}-.0449601{col 87}{space 3} .0383605
{txt}{space 30}2  {c |}{col 34}{res}{space 2} .0119996{col 46}{space 2}  .022486{col 57}{space 1}    0.53{col 66}{space 3}0.595{col 74}{space 4}-.0325909{col 87}{space 3} .0565902
{txt}{space 32} {c |}
{space 8}ln_ratio_fem_tot_men_tot {c |}{col 34}{res}{space 2}-.0056168{col 46}{space 2} .0555009{col 57}{space 1}   -0.10{col 66}{space 3}0.920{col 74}{space 4}-.1156771{col 87}{space 3} .1044435
{txt}{space 24}minority {c |}{col 34}{res}{space 2}-.0767909{col 46}{space 2} .0036169{col 57}{space 1}  -21.23{col 66}{space 3}0.000{col 74}{space 4}-.0839633{col 87}{space 3}-.0696185
{txt}{space 22}supervisor {c |}{col 34}{res}{space 2} .1272702{col 46}{space 2} .0074355{col 57}{space 1}   17.12{col 66}{space 3}0.000{col 74}{space 4} .1125253{col 87}{space 3} .1420151
{txt}{space 18}topoffgender_2 {c |}{col 34}{res}{space 2}-.0028588{col 46}{space 2} .0045063{col 57}{space 1}   -0.63{col 66}{space 3}0.527{col 74}{space 4} -.011795{col 87}{space 3} .0060774
{txt}{space 12}lntotworkforce_count {c |}{col 34}{res}{space 2} .0750682{col 46}{space 2} .0323854{col 57}{space 1}    2.32{col 66}{space 3}0.022{col 74}{space 4} .0108468{col 87}{space 3} .1392896
{txt}{space 4}ln_professionals_total_ratio {c |}{col 34}{res}{space 2} .0077249{col 46}{space 2} .0415587{col 57}{space 1}    0.19{col 66}{space 3}0.853{col 74}{space 4}-.0746876{col 87}{space 3} .0901374
{txt}{space 32} {c |}
{space 24}agencyid {c |}
{space 30}2  {c |}{col 34}{res}{space 2} .3054817{col 46}{space 2} .1144392{col 57}{space 1}    2.67{col 66}{space 3}0.009{col 74}{space 4} .0785446{col 87}{space 3} .5324189
{txt}{space 30}3  {c |}{col 34}{res}{space 2}  .089258{col 46}{space 2} .0540533{col 57}{space 1}    1.65{col 66}{space 3}0.102{col 74}{space 4}-.0179318{col 87}{space 3} .1964478
{txt}{space 30}4  {c |}{col 34}{res}{space 2} .4306732{col 46}{space 2} .1507573{col 57}{space 1}    2.86{col 66}{space 3}0.005{col 74}{space 4} .1317159{col 87}{space 3} .7296305
{txt}{space 30}5  {c |}{col 34}{res}{space 2} .2620605{col 46}{space 2} .1044604{col 57}{space 1}    2.51{col 66}{space 3}0.014{col 74}{space 4} .0549116{col 87}{space 3} .4692095
{txt}{space 30}6  {c |}{col 34}{res}{space 2} .2482645{col 46}{space 2} .1105301{col 57}{space 1}    2.25{col 66}{space 3}0.027{col 74}{space 4} .0290792{col 87}{space 3} .4674497
{txt}{space 30}7  {c |}{col 34}{res}{space 2} .3557466{col 46}{space 2}  .182504{col 57}{space 1}    1.95{col 66}{space 3}0.054{col 74}{space 4}-.0061657{col 87}{space 3} .7176589
{txt}{space 30}8  {c |}{col 34}{res}{space 2} .3002694{col 46}{space 2} .1425007{col 57}{space 1}    2.11{col 66}{space 3}0.038{col 74}{space 4} .0176852{col 87}{space 3} .5828537
{txt}{space 30}9  {c |}{col 34}{res}{space 2}-.0122595{col 46}{space 2} .0227092{col 57}{space 1}   -0.54{col 66}{space 3}0.590{col 74}{space 4}-.0572926{col 87}{space 3} .0327736
{txt}{space 29}10  {c |}{col 34}{res}{space 2} .2486357{col 46}{space 2} .1616721{col 57}{space 1}    1.54{col 66}{space 3}0.127{col 74}{space 4}-.0719662{col 87}{space 3} .5692376
{txt}{space 29}11  {c |}{col 34}{res}{space 2} .2131643{col 46}{space 2} .1179662{col 57}{space 1}    1.81{col 66}{space 3}0.074{col 74}{space 4}-.0207671{col 87}{space 3} .4470956
{txt}{space 29}12  {c |}{col 34}{res}{space 2} .3723079{col 46}{space 2} .1712346{col 57}{space 1}    2.17{col 66}{space 3}0.032{col 74}{space 4} .0327433{col 87}{space 3} .7118726
{txt}{space 29}13  {c |}{col 34}{res}{space 2} .3566036{col 46}{space 2} .1436762{col 57}{space 1}    2.48{col 66}{space 3}0.015{col 74}{space 4} .0716883{col 87}{space 3} .6415189
{txt}{space 29}14  {c |}{col 34}{res}{space 2} .1616508{col 46}{space 2} .1055922{col 57}{space 1}    1.53{col 66}{space 3}0.129{col 74}{space 4}-.0477424{col 87}{space 3}  .371044
{txt}{space 29}15  {c |}{col 34}{res}{space 2} .2996949{col 46}{space 2} .1163998{col 57}{space 1}    2.57{col 66}{space 3}0.011{col 74}{space 4} .0688697{col 87}{space 3} .5305201
{txt}{space 29}16  {c |}{col 34}{res}{space 2} .4743015{col 46}{space 2} .1969173{col 57}{space 1}    2.41{col 66}{space 3}0.018{col 74}{space 4}  .083807{col 87}{space 3}  .864796
{txt}{space 29}17  {c |}{col 34}{res}{space 2} .1296542{col 46}{space 2} .1578167{col 57}{space 1}    0.82{col 66}{space 3}0.413{col 74}{space 4}-.1833022{col 87}{space 3} .4426106
{txt}{space 29}18  {c |}{col 34}{res}{space 2} .3543586{col 46}{space 2} .1524883{col 57}{space 1}    2.32{col 66}{space 3}0.022{col 74}{space 4} .0519686{col 87}{space 3} .6567487
{txt}{space 29}19  {c |}{col 34}{res}{space 2} .2217945{col 46}{space 2} .0986462{col 57}{space 1}    2.25{col 66}{space 3}0.027{col 74}{space 4} .0261754{col 87}{space 3} .4174136
{txt}{space 29}20  {c |}{col 34}{res}{space 2} .2980108{col 46}{space 2}  .158459{col 57}{space 1}    1.88{col 66}{space 3}0.063{col 74}{space 4}-.0162193{col 87}{space 3} .6122409
{txt}{space 29}21  {c |}{col 34}{res}{space 2} .2673297{col 46}{space 2} .1190513{col 57}{space 1}    2.25{col 66}{space 3}0.027{col 74}{space 4} .0312465{col 87}{space 3}  .503413
{txt}{space 29}22  {c |}{col 34}{res}{space 2} .2683585{col 46}{space 2} .1436636{col 57}{space 1}    1.87{col 66}{space 3}0.065{col 74}{space 4}-.0165318{col 87}{space 3} .5532487
{txt}{space 29}23  {c |}{col 34}{res}{space 2}-.0855321{col 46}{space 2} .0512426{col 57}{space 1}   -1.67{col 66}{space 3}0.098{col 74}{space 4} -.187148{col 87}{space 3} .0160838
{txt}{space 29}24  {c |}{col 34}{res}{space 2} .2935572{col 46}{space 2} .0961512{col 57}{space 1}    3.05{col 66}{space 3}0.003{col 74}{space 4} .1028859{col 87}{space 3} .4842286
{txt}{space 29}25  {c |}{col 34}{res}{space 2} .1964073{col 46}{space 2} .1353541{col 57}{space 1}    1.45{col 66}{space 3}0.150{col 74}{space 4}-.0720049{col 87}{space 3} .4648196
{txt}{space 29}26  {c |}{col 34}{res}{space 2} .1014572{col 46}{space 2} .1111094{col 57}{space 1}    0.91{col 66}{space 3}0.363{col 74}{space 4} -.118877{col 87}{space 3} .3217914
{txt}{space 29}27  {c |}{col 34}{res}{space 2} .3877082{col 46}{space 2} .1579253{col 57}{space 1}    2.46{col 66}{space 3}0.016{col 74}{space 4} .0745363{col 87}{space 3}   .70088
{txt}{space 29}28  {c |}{col 34}{res}{space 2} .0033277{col 46}{space 2} .0729461{col 57}{space 1}    0.05{col 66}{space 3}0.964{col 74}{space 4}-.1413272{col 87}{space 3} .1479826
{txt}{space 29}29  {c |}{col 34}{res}{space 2} .1082834{col 46}{space 2} .1309702{col 57}{space 1}    0.83{col 66}{space 3}0.410{col 74}{space 4}-.1514354{col 87}{space 3} .3680023
{txt}{space 29}30  {c |}{col 34}{res}{space 2} .1440809{col 46}{space 2} .1218755{col 57}{space 1}    1.18{col 66}{space 3}0.240{col 74}{space 4}-.0976028{col 87}{space 3} .3857645
{txt}{space 29}31  {c |}{col 34}{res}{space 2}-.0130883{col 46}{space 2} .1462473{col 57}{space 1}   -0.09{col 66}{space 3}0.929{col 74}{space 4}-.3031022{col 87}{space 3} .2769255
{txt}{space 29}32  {c |}{col 34}{res}{space 2} .2499107{col 46}{space 2} .1132154{col 57}{space 1}    2.21{col 66}{space 3}0.029{col 74}{space 4} .0254003{col 87}{space 3} .4744211
{txt}{space 29}33  {c |}{col 34}{res}{space 2} .1506377{col 46}{space 2} .0692237{col 57}{space 1}    2.18{col 66}{space 3}0.032{col 74}{space 4} .0133645{col 87}{space 3} .2879108
{txt}{space 29}34  {c |}{col 34}{res}{space 2} .1502034{col 46}{space 2} .1201603{col 57}{space 1}    1.25{col 66}{space 3}0.214{col 74}{space 4}-.0880789{col 87}{space 3} .3884857
{txt}{space 29}35  {c |}{col 34}{res}{space 2}  .185379{col 46}{space 2} .0940268{col 57}{space 1}    1.97{col 66}{space 3}0.051{col 74}{space 4}-.0010796{col 87}{space 3} .3718377
{txt}{space 29}36  {c |}{col 34}{res}{space 2} .2429218{col 46}{space 2} .1180458{col 57}{space 1}    2.06{col 66}{space 3}0.042{col 74}{space 4} .0088325{col 87}{space 3} .4770111
{txt}{space 29}37  {c |}{col 34}{res}{space 2} .2386051{col 46}{space 2} .1116477{col 57}{space 1}    2.14{col 66}{space 3}0.035{col 74}{space 4} .0172035{col 87}{space 3} .4600067
{txt}{space 29}38  {c |}{col 34}{res}{space 2} .3887356{col 46}{space 2} .1632598{col 57}{space 1}    2.38{col 66}{space 3}0.019{col 74}{space 4} .0649854{col 87}{space 3} .7124859
{txt}{space 29}39  {c |}{col 34}{res}{space 2} .2148234{col 46}{space 2} .1155648{col 57}{space 1}    1.86{col 66}{space 3}0.066{col 74}{space 4}-.0143459{col 87}{space 3} .4439927
{txt}{space 29}40  {c |}{col 34}{res}{space 2} .0295705{col 46}{space 2} .0720455{col 57}{space 1}    0.41{col 66}{space 3}0.682{col 74}{space 4}-.1132984{col 87}{space 3} .1724393
{txt}{space 29}41  {c |}{col 34}{res}{space 2} .3033804{col 46}{space 2} .1477272{col 57}{space 1}    2.05{col 66}{space 3}0.043{col 74}{space 4} .0104318{col 87}{space 3} .5963291
{txt}{space 29}42  {c |}{col 34}{res}{space 2} .3176812{col 46}{space 2} .1220668{col 57}{space 1}    2.60{col 66}{space 3}0.011{col 74}{space 4} .0756181{col 87}{space 3} .5597442
{txt}{space 29}43  {c |}{col 34}{res}{space 2} .1064172{col 46}{space 2} .0475443{col 57}{space 1}    2.24{col 66}{space 3}0.027{col 74}{space 4} .0121351{col 87}{space 3} .2006994
{txt}{space 29}44  {c |}{col 34}{res}{space 2} .3520563{col 46}{space 2} .1032821{col 57}{space 1}    3.41{col 66}{space 3}0.001{col 74}{space 4} .1472439{col 87}{space 3} .5568686
{txt}{space 29}45  {c |}{col 34}{res}{space 2} .3007054{col 46}{space 2} .1228888{col 57}{space 1}    2.45{col 66}{space 3}0.016{col 74}{space 4} .0570122{col 87}{space 3} .5443986
{txt}{space 29}46  {c |}{col 34}{res}{space 2}  .283628{col 46}{space 2} .1873454{col 57}{space 1}    1.51{col 66}{space 3}0.133{col 74}{space 4}-.0878849{col 87}{space 3}  .655141
{txt}{space 29}47  {c |}{col 34}{res}{space 2} .2041208{col 46}{space 2} .0864247{col 57}{space 1}    2.36{col 66}{space 3}0.020{col 74}{space 4} .0327374{col 87}{space 3} .3755042
{txt}{space 29}48  {c |}{col 34}{res}{space 2}  .229872{col 46}{space 2} .1338469{col 57}{space 1}    1.72{col 66}{space 3}0.089{col 74}{space 4}-.0355513{col 87}{space 3} .4952954
{txt}{space 29}49  {c |}{col 34}{res}{space 2}  .442505{col 46}{space 2} .1920017{col 57}{space 1}    2.30{col 66}{space 3}0.023{col 74}{space 4} .0617584{col 87}{space 3} .8232516
{txt}{space 29}50  {c |}{col 34}{res}{space 2} .4202305{col 46}{space 2} .1595169{col 57}{space 1}    2.63{col 66}{space 3}0.010{col 74}{space 4} .1039025{col 87}{space 3} .7365585
{txt}{space 29}51  {c |}{col 34}{res}{space 2}  .371371{col 46}{space 2} .1905822{col 57}{space 1}    1.95{col 66}{space 3}0.054{col 74}{space 4}-.0065607{col 87}{space 3} .7493027
{txt}{space 29}52  {c |}{col 34}{res}{space 2} .3356493{col 46}{space 2} .1822793{col 57}{space 1}    1.84{col 66}{space 3}0.068{col 74}{space 4}-.0258175{col 87}{space 3}  .697116
{txt}{space 29}53  {c |}{col 34}{res}{space 2} .3021397{col 46}{space 2} .1355435{col 57}{space 1}    2.23{col 66}{space 3}0.028{col 74}{space 4} .0333518{col 87}{space 3} .5709275
{txt}{space 29}54  {c |}{col 34}{res}{space 2} .3422816{col 46}{space 2} .1532282{col 57}{space 1}    2.23{col 66}{space 3}0.028{col 74}{space 4} .0384244{col 87}{space 3} .6461388
{txt}{space 29}55  {c |}{col 34}{res}{space 2} .5330813{col 46}{space 2} .2134049{col 57}{space 1}    2.50{col 66}{space 3}0.014{col 74}{space 4} .1098914{col 87}{space 3} .9562713
{txt}{space 29}56  {c |}{col 34}{res}{space 2} .2968665{col 46}{space 2}  .199767{col 57}{space 1}    1.49{col 66}{space 3}0.140{col 74}{space 4}-.0992789{col 87}{space 3} .6930119
{txt}{space 29}57  {c |}{col 34}{res}{space 2} .4055538{col 46}{space 2} .2310988{col 57}{space 1}    1.75{col 66}{space 3}0.082{col 74}{space 4}-.0527237{col 87}{space 3} .8638313
{txt}{space 29}58  {c |}{col 34}{res}{space 2} .2960132{col 46}{space 2} .1508445{col 57}{space 1}    1.96{col 66}{space 3}0.052{col 74}{space 4}-.0031171{col 87}{space 3} .5951436
{txt}{space 29}59  {c |}{col 34}{res}{space 2} .3377024{col 46}{space 2} .1706876{col 57}{space 1}    1.98{col 66}{space 3}0.051{col 74}{space 4}-.0007775{col 87}{space 3} .6761822
{txt}{space 29}60  {c |}{col 34}{res}{space 2} .1816783{col 46}{space 2} .0934242{col 57}{space 1}    1.94{col 66}{space 3}0.055{col 74}{space 4}-.0035855{col 87}{space 3}  .366942
{txt}{space 29}61  {c |}{col 34}{res}{space 2} .1846867{col 46}{space 2} .1064558{col 57}{space 1}    1.73{col 66}{space 3}0.086{col 74}{space 4}-.0264191{col 87}{space 3} .3957925
{txt}{space 29}62  {c |}{col 34}{res}{space 2}  .394775{col 46}{space 2} .1730764{col 57}{space 1}    2.28{col 66}{space 3}0.025{col 74}{space 4}  .051558{col 87}{space 3}  .737992
{txt}{space 29}63  {c |}{col 34}{res}{space 2} .4556611{col 46}{space 2} .1712959{col 57}{space 1}    2.66{col 66}{space 3}0.009{col 74}{space 4} .1159749{col 87}{space 3} .7953473
{txt}{space 29}64  {c |}{col 34}{res}{space 2} .4575463{col 46}{space 2} .1864309{col 57}{space 1}    2.45{col 66}{space 3}0.016{col 74}{space 4}  .087847{col 87}{space 3} .8272457
{txt}{space 29}65  {c |}{col 34}{res}{space 2} .2707272{col 46}{space 2} .1027045{col 57}{space 1}    2.64{col 66}{space 3}0.010{col 74}{space 4} .0670603{col 87}{space 3} .4743941
{txt}{space 29}66  {c |}{col 34}{res}{space 2} .3206529{col 46}{space 2} .2036342{col 57}{space 1}    1.57{col 66}{space 3}0.118{col 74}{space 4}-.0831614{col 87}{space 3} .7244673
{txt}{space 29}67  {c |}{col 34}{res}{space 2} .3267874{col 46}{space 2} .1318193{col 57}{space 1}    2.48{col 66}{space 3}0.015{col 74}{space 4} .0653847{col 87}{space 3}   .58819
{txt}{space 29}68  {c |}{col 34}{res}{space 2}   .31517{col 46}{space 2} .1488683{col 57}{space 1}    2.12{col 66}{space 3}0.037{col 74}{space 4} .0199587{col 87}{space 3} .6103814
{txt}{space 29}69  {c |}{col 34}{res}{space 2} .1936131{col 46}{space 2} .1139231{col 57}{space 1}    1.70{col 66}{space 3}0.092{col 74}{space 4}-.0323007{col 87}{space 3} .4195269
{txt}{space 29}70  {c |}{col 34}{res}{space 2} .4111402{col 46}{space 2}  .186938{col 57}{space 1}    2.20{col 66}{space 3}0.030{col 74}{space 4} .0404351{col 87}{space 3} .7818454
{txt}{space 29}71  {c |}{col 34}{res}{space 2} .1187729{col 46}{space 2} .1374836{col 57}{space 1}    0.86{col 66}{space 3}0.390{col 74}{space 4}-.1538621{col 87}{space 3}  .391408
{txt}{space 29}72  {c |}{col 34}{res}{space 2} .2738404{col 46}{space 2} .1117486{col 57}{space 1}    2.45{col 66}{space 3}0.016{col 74}{space 4} .0522387{col 87}{space 3} .4954421
{txt}{space 29}73  {c |}{col 34}{res}{space 2} .4905309{col 46}{space 2} .1688042{col 57}{space 1}    2.91{col 66}{space 3}0.004{col 74}{space 4} .1557858{col 87}{space 3} .8252759
{txt}{space 29}74  {c |}{col 34}{res}{space 2} .0953999{col 46}{space 2} .1080451{col 57}{space 1}    0.88{col 66}{space 3}0.379{col 74}{space 4}-.1188575{col 87}{space 3} .3096573
{txt}{space 29}75  {c |}{col 34}{res}{space 2} .1919343{col 46}{space 2} .1279097{col 57}{space 1}    1.50{col 66}{space 3}0.137{col 74}{space 4}-.0617155{col 87}{space 3}  .445584
{txt}{space 29}76  {c |}{col 34}{res}{space 2} .3342169{col 46}{space 2} .1536352{col 57}{space 1}    2.18{col 66}{space 3}0.032{col 74}{space 4} .0295525{col 87}{space 3} .6388813
{txt}{space 29}77  {c |}{col 34}{res}{space 2} .2632399{col 46}{space 2} .1457599{col 57}{space 1}    1.81{col 66}{space 3}0.074{col 74}{space 4}-.0258074{col 87}{space 3} .5522872
{txt}{space 29}78  {c |}{col 34}{res}{space 2} .2950194{col 46}{space 2} .0987533{col 57}{space 1}    2.99{col 66}{space 3}0.004{col 74}{space 4} .0991879{col 87}{space 3} .4908509
{txt}{space 29}79  {c |}{col 34}{res}{space 2}-.0137223{col 46}{space 2} .0164497{col 57}{space 1}   -0.83{col 66}{space 3}0.406{col 74}{space 4}-.0463427{col 87}{space 3} .0188981
{txt}{space 29}80  {c |}{col 34}{res}{space 2} .4327542{col 46}{space 2} .1729893{col 57}{space 1}    2.50{col 66}{space 3}0.014{col 74}{space 4}   .08971{col 87}{space 3} .7757985
{txt}{space 29}81  {c |}{col 34}{res}{space 2} .2115786{col 46}{space 2} .1779019{col 57}{space 1}    1.19{col 66}{space 3}0.237{col 74}{space 4}-.1412075{col 87}{space 3} .5643648
{txt}{space 29}82  {c |}{col 34}{res}{space 2} .3534204{col 46}{space 2} .1843787{col 57}{space 1}    1.92{col 66}{space 3}0.058{col 74}{space 4}-.0122095{col 87}{space 3} .7190502
{txt}{space 29}83  {c |}{col 34}{res}{space 2} .4284467{col 46}{space 2} .1453094{col 57}{space 1}    2.95{col 66}{space 3}0.004{col 74}{space 4} .1402926{col 87}{space 3} .7166007
{txt}{space 29}84  {c |}{col 34}{res}{space 2} .3311847{col 46}{space 2}  .184548{col 57}{space 1}    1.79{col 66}{space 3}0.076{col 74}{space 4}-.0347809{col 87}{space 3} .6971503
{txt}{space 29}85  {c |}{col 34}{res}{space 2} .4054784{col 46}{space 2} .1471784{col 57}{space 1}    2.76{col 66}{space 3}0.007{col 74}{space 4} .1136181{col 87}{space 3} .6973386
{txt}{space 29}86  {c |}{col 34}{res}{space 2} .4636011{col 46}{space 2}  .189664{col 57}{space 1}    2.44{col 66}{space 3}0.016{col 74}{space 4} .0874902{col 87}{space 3}  .839712
{txt}{space 29}87  {c |}{col 34}{res}{space 2} .4661883{col 46}{space 2} .1909561{col 57}{space 1}    2.44{col 66}{space 3}0.016{col 74}{space 4} .0875152{col 87}{space 3} .8448615
{txt}{space 29}88  {c |}{col 34}{res}{space 2} .2540349{col 46}{space 2} .1350659{col 57}{space 1}    1.88{col 66}{space 3}0.063{col 74}{space 4}-.0138059{col 87}{space 3} .5218757
{txt}{space 29}89  {c |}{col 34}{res}{space 2} .2983005{col 46}{space 2} .1458304{col 57}{space 1}    2.05{col 66}{space 3}0.043{col 74}{space 4} .0091133{col 87}{space 3} .5874877
{txt}{space 29}90  {c |}{col 34}{res}{space 2} .0787042{col 46}{space 2} .1088477{col 57}{space 1}    0.72{col 66}{space 3}0.471{col 74}{space 4}-.1371447{col 87}{space 3} .2945532
{txt}{space 29}91  {c |}{col 34}{res}{space 2} .1943677{col 46}{space 2} .1092955{col 57}{space 1}    1.78{col 66}{space 3}0.078{col 74}{space 4}-.0223694{col 87}{space 3} .4111048
{txt}{space 29}92  {c |}{col 34}{res}{space 2} .0801574{col 46}{space 2} .0446879{col 57}{space 1}    1.79{col 66}{space 3}0.076{col 74}{space 4}-.0084604{col 87}{space 3} .1687752
{txt}{space 29}93  {c |}{col 34}{res}{space 2} .4277423{col 46}{space 2} .1463755{col 57}{space 1}    2.92{col 66}{space 3}0.004{col 74}{space 4} .1374742{col 87}{space 3} .7180103
{txt}{space 29}94  {c |}{col 34}{res}{space 2} .4625888{col 46}{space 2} .1666656{col 57}{space 1}    2.78{col 66}{space 3}0.007{col 74}{space 4} .1320847{col 87}{space 3} .7930928
{txt}{space 29}95  {c |}{col 34}{res}{space 2} .2168759{col 46}{space 2} .1444668{col 57}{space 1}    1.50{col 66}{space 3}0.136{col 74}{space 4}-.0696071{col 87}{space 3} .5033589
{txt}{space 29}96  {c |}{col 34}{res}{space 2} .3398681{col 46}{space 2} .1542732{col 57}{space 1}    2.20{col 66}{space 3}0.030{col 74}{space 4} .0339386{col 87}{space 3} .6457977
{txt}{space 29}97  {c |}{col 34}{res}{space 2} .3949283{col 46}{space 2} .1483518{col 57}{space 1}    2.66{col 66}{space 3}0.009{col 74}{space 4} .1007412{col 87}{space 3} .6891155
{txt}{space 29}98  {c |}{col 34}{res}{space 2} .5581648{col 46}{space 2} .1840092{col 57}{space 1}    3.03{col 66}{space 3}0.003{col 74}{space 4} .1932676{col 87}{space 3} .9230621
{txt}{space 29}99  {c |}{col 34}{res}{space 2}  .089942{col 46}{space 2} .0916572{col 57}{space 1}    0.98{col 66}{space 3}0.329{col 74}{space 4}-.0918177{col 87}{space 3} .2717017
{txt}{space 28}100  {c |}{col 34}{res}{space 2} .2514462{col 46}{space 2} .1483316{col 57}{space 1}    1.70{col 66}{space 3}0.093{col 74}{space 4} -.042701{col 87}{space 3} .5455935
{txt}{space 28}101  {c |}{col 34}{res}{space 2} .4042816{col 46}{space 2} .1341575{col 57}{space 1}    3.01{col 66}{space 3}0.003{col 74}{space 4} .1382423{col 87}{space 3} .6703209
{txt}{space 28}102  {c |}{col 34}{res}{space 2} .2541871{col 46}{space 2} .1534978{col 57}{space 1}    1.66{col 66}{space 3}0.101{col 74}{space 4}-.0502048{col 87}{space 3} .5585791
{txt}{space 28}103  {c |}{col 34}{res}{space 2} .0725977{col 46}{space 2} .1050734{col 57}{space 1}    0.69{col 66}{space 3}0.491{col 74}{space 4}-.1357669{col 87}{space 3} .2809623
{txt}{space 28}104  {c |}{col 34}{res}{space 2}-.1011645{col 46}{space 2} .0750058{col 57}{space 1}   -1.35{col 66}{space 3}0.180{col 74}{space 4}-.2499039{col 87}{space 3} .0475749
{txt}{space 28}105  {c |}{col 34}{res}{space 2} .3348189{col 46}{space 2} .1526483{col 57}{space 1}    2.19{col 66}{space 3}0.031{col 74}{space 4} .0321115{col 87}{space 3} .6375263
{txt}{space 32} {c |}
{space 28}year {c |}
{space 27}2011  {c |}{col 34}{res}{space 2}-.0041428{col 46}{space 2} .0032366{col 57}{space 1}   -1.28{col 66}{space 3}0.203{col 74}{space 4}-.0105611{col 87}{space 3} .0022755
{txt}{space 27}2012  {c |}{col 34}{res}{space 2} .0000201{col 46}{space 2} .0044925{col 57}{space 1}    0.00{col 66}{space 3}0.996{col 74}{space 4}-.0088887{col 87}{space 3} .0089289
{txt}{space 27}2013  {c |}{col 34}{res}{space 2}-.0010903{col 46}{space 2} .0049916{col 57}{space 1}   -0.22{col 66}{space 3}0.828{col 74}{space 4}-.0109888{col 87}{space 3} .0088082
{txt}{space 27}2014  {c |}{col 34}{res}{space 2}-.0071208{col 46}{space 2}  .007045{col 57}{space 1}   -1.01{col 66}{space 3}0.314{col 74}{space 4}-.0210914{col 87}{space 3} .0068498
{txt}{space 27}2015  {c |}{col 34}{res}{space 2}-.0146831{col 46}{space 2} .0085962{col 57}{space 1}   -1.71{col 66}{space 3}0.091{col 74}{space 4}-.0317298{col 87}{space 3} .0023636
{txt}{space 27}2016  {c |}{col 34}{res}{space 2}-.0179585{col 46}{space 2} .0074209{col 57}{space 1}   -2.42{col 66}{space 3}0.017{col 74}{space 4}-.0326744{col 87}{space 3}-.0032425
{txt}{space 27}2017  {c |}{col 34}{res}{space 2} -.003732{col 46}{space 2}  .009602{col 57}{space 1}   -0.39{col 66}{space 3}0.698{col 74}{space 4} -.022773{col 87}{space 3} .0153091
{txt}{space 27}2018  {c |}{col 34}{res}{space 2}-.0328521{col 46}{space 2} .0073676{col 57}{space 1}   -4.46{col 66}{space 3}0.000{col 74}{space 4}-.0474622{col 87}{space 3}-.0182419
{txt}{space 27}2019  {c |}{col 34}{res}{space 2}-.0711104{col 46}{space 2} .0084424{col 57}{space 1}   -8.42{col 66}{space 3}0.000{col 74}{space 4} -.087852{col 87}{space 3}-.0543687
{txt}{space 32} {c |}
{space 27}_cons {c |}{col 34}{res}{space 2}-.1276648{col 46}{space 2} .4155547{col 57}{space 1}   -0.31{col 66}{space 3}0.759{col 74}{space 4}-.9517254{col 87}{space 3} .6963958
{txt}{hline 33}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891027{col 50}    20{col 58}  3782095{col 69}  3782349
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1514916{col 26}{space 2} .0418288{col 37}{space 1}    3.62{col 46}{space 3}0.000{col 54}{space 4} .0685435{col 67}{space 3} .2344396
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0032998{col 26}{space 2} .0210083{col 37}{space 1}   -0.16{col 46}{space 3}0.875{col 54}{space 4}-.0449601{col 67}{space 3} .0383605
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0119996{col 26}{space 2}  .022486{col 37}{space 1}    0.53{col 46}{space 3}0.595{col 54}{space 4}-.0325909{col 67}{space 3} .0565902
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub -  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0152995{col 26}{space 2} .0181708{col 37}{space 1}    0.84{col 46}{space 3}0.402{col 54}{space 4}-.0207339{col 67}{space 3} .0513328
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
.    
. *** MODEL 4: CONDITIONAL RESPONSES BY MINORITY WOMEN VERSUS MINORITY MEN [BASELINE CATEGORY: NON-MINORITY RESPONDENTS] -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority_het   ln_ratio_min_tot_nmin_tot    gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year if e(sample), vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(19, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0406
                                                {txt}Root MSE          =    {res} .51448

{txt}{ralign 103:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 38}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 39}{c |}{col 51}    Robust
{col 1}                  lndiversity2zeroadj{col 39}{c |} Coefficient{col 51}  std. err.{col 63}      t{col 71}   P>|t|{col 79}     [95% con{col 92}f. interval]
{hline 38}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}ln_ratio_mnmsup_mnmsub {c |}{col 39}{res}{space 2} .0535774{col 51}{space 2} .0340399{col 62}{space 1}    1.57{col 71}{space 3}0.119{col 79}{space 4}-.0139249{col 92}{space 3} .1210798
{txt}{space 37} {c |}
{space 25}minority_het {c |}
{space 35}1  {c |}{col 39}{res}{space 2}-.0677496{col 51}{space 2} .0056097{col 62}{space 1}  -12.08{col 71}{space 3}0.000{col 79}{space 4}-.0788737{col 92}{space 3}-.0566254
{txt}{space 35}2  {c |}{col 39}{res}{space 2}-.0945171{col 51}{space 2} .0069713{col 62}{space 1}  -13.56{col 71}{space 3}0.000{col 79}{space 4}-.1083415{col 92}{space 3}-.0806928
{txt}{space 37} {c |}
minority_het#c.ln_ratio_mnmsup_mnmsub {c |}
{space 35}1  {c |}{col 39}{res}{space 2} .0270159{col 51}{space 2} .0151078{col 62}{space 1}    1.79{col 71}{space 3}0.077{col 79}{space 4}-.0029434{col 92}{space 3} .0569753
{txt}{space 35}2  {c |}{col 39}{res}{space 2} .0543246{col 51}{space 2} .0185932{col 62}{space 1}    2.92{col 71}{space 3}0.004{col 79}{space 4} .0174537{col 92}{space 3} .0911956
{txt}{space 37} {c |}
{space 12}ln_ratio_min_tot_nmin_tot {c |}{col 39}{res}{space 2} .0535216{col 51}{space 2} .0450063{col 62}{space 1}    1.19{col 71}{space 3}0.237{col 79}{space 4}-.0357275{col 92}{space 3} .1427707
{txt}{space 31}gender {c |}{col 39}{res}{space 2}-.0269575{col 51}{space 2} .0045051{col 62}{space 1}   -5.98{col 71}{space 3}0.000{col 79}{space 4}-.0358914{col 92}{space 3}-.0180237
{txt}{space 27}supervisor {c |}{col 39}{res}{space 2} .1273969{col 51}{space 2} .0074145{col 62}{space 1}   17.18{col 71}{space 3}0.000{col 79}{space 4} .1126936{col 92}{space 3} .1421002
{txt}{space 21}topoffminority_2 {c |}{col 39}{res}{space 2}  .007532{col 51}{space 2} .0059288{col 62}{space 1}    1.27{col 71}{space 3}0.207{col 79}{space 4} -.004225{col 92}{space 3} .0192891
{txt}{space 17}lntotworkforce_count {c |}{col 39}{res}{space 2} .0649795{col 51}{space 2} .0402232{col 62}{space 1}    1.62{col 71}{space 3}0.109{col 79}{space 4}-.0147846{col 92}{space 3} .1447436
{txt}{space 9}ln_professionals_total_ratio {c |}{col 39}{res}{space 2}  .021779{col 51}{space 2} .0503212{col 62}{space 1}    0.43{col 71}{space 3}0.666{col 79}{space 4}-.0780098{col 92}{space 3} .1215679
{txt}{space 37} {c |}
{space 29}agencyid {c |}
{space 35}2  {c |}{col 39}{res}{space 2} .2116284{col 51}{space 2} .1223985{col 62}{space 1}    1.73{col 71}{space 3}0.087{col 79}{space 4}-.0310925{col 92}{space 3} .4543492
{txt}{space 35}3  {c |}{col 39}{res}{space 2} .0331383{col 51}{space 2} .0540882{col 62}{space 1}    0.61{col 71}{space 3}0.541{col 79}{space 4}-.0741207{col 92}{space 3} .1403973
{txt}{space 35}4  {c |}{col 39}{res}{space 2} .2818834{col 51}{space 2} .1640651{col 62}{space 1}    1.72{col 71}{space 3}0.089{col 79}{space 4}-.0434638{col 92}{space 3} .6072305
{txt}{space 35}5  {c |}{col 39}{res}{space 2} .1682204{col 51}{space 2} .1272218{col 62}{space 1}    1.32{col 71}{space 3}0.189{col 79}{space 4}-.0840652{col 92}{space 3}  .420506
{txt}{space 35}6  {c |}{col 39}{res}{space 2} .1739746{col 51}{space 2}  .118517{col 62}{space 1}    1.47{col 71}{space 3}0.145{col 79}{space 4}-.0610489{col 92}{space 3} .4089982
{txt}{space 35}7  {c |}{col 39}{res}{space 2} .2458642{col 51}{space 2} .2170299{col 62}{space 1}    1.13{col 71}{space 3}0.260{col 79}{space 4}-.1845142{col 92}{space 3} .6762427
{txt}{space 35}8  {c |}{col 39}{res}{space 2} .2329112{col 51}{space 2} .1624358{col 62}{space 1}    1.43{col 71}{space 3}0.155{col 79}{space 4} -.089205{col 92}{space 3} .5550275
{txt}{space 35}9  {c |}{col 39}{res}{space 2} -.055834{col 51}{space 2} .0229801{col 62}{space 1}   -2.43{col 71}{space 3}0.017{col 79}{space 4}-.1014044{col 92}{space 3}-.0102635
{txt}{space 34}10  {c |}{col 39}{res}{space 2} .1898612{col 51}{space 2} .2310786{col 62}{space 1}    0.82{col 71}{space 3}0.413{col 79}{space 4}-.2683763{col 92}{space 3} .6480988
{txt}{space 34}11  {c |}{col 39}{res}{space 2} .1601544{col 51}{space 2} .1046703{col 62}{space 1}    1.53{col 71}{space 3}0.129{col 79}{space 4}-.0474107{col 92}{space 3} .3677195
{txt}{space 34}12  {c |}{col 39}{res}{space 2} .3166313{col 51}{space 2} .2146208{col 62}{space 1}    1.48{col 71}{space 3}0.143{col 79}{space 4}-.1089698{col 92}{space 3} .7422324
{txt}{space 34}13  {c |}{col 39}{res}{space 2} .3141914{col 51}{space 2} .1625478{col 62}{space 1}    1.93{col 71}{space 3}0.056{col 79}{space 4} -.008147{col 92}{space 3} .6365299
{txt}{space 34}14  {c |}{col 39}{res}{space 2} .1573085{col 51}{space 2} .1100498{col 62}{space 1}    1.43{col 71}{space 3}0.156{col 79}{space 4}-.0609244{col 92}{space 3} .3755413
{txt}{space 34}15  {c |}{col 39}{res}{space 2} .2328675{col 51}{space 2} .1542313{col 62}{space 1}    1.51{col 71}{space 3}0.134{col 79}{space 4}-.0729791{col 92}{space 3}  .538714
{txt}{space 34}16  {c |}{col 39}{res}{space 2} .2060345{col 51}{space 2} .2875131{col 62}{space 1}    0.72{col 71}{space 3}0.475{col 79}{space 4}-.3641147{col 92}{space 3} .7761838
{txt}{space 34}17  {c |}{col 39}{res}{space 2} .0452174{col 51}{space 2} .1879359{col 62}{space 1}    0.24{col 71}{space 3}0.810{col 79}{space 4}-.3274665{col 92}{space 3} .4179014
{txt}{space 34}18  {c |}{col 39}{res}{space 2} .3085627{col 51}{space 2} .1692415{col 62}{space 1}    1.82{col 71}{space 3}0.071{col 79}{space 4}-.0270495{col 92}{space 3}  .644175
{txt}{space 34}19  {c |}{col 39}{res}{space 2} .1793218{col 51}{space 2} .1144403{col 62}{space 1}    1.57{col 71}{space 3}0.120{col 79}{space 4}-.0476176{col 92}{space 3} .4062613
{txt}{space 34}20  {c |}{col 39}{res}{space 2} .0590682{col 51}{space 2} .1201706{col 62}{space 1}    0.49{col 71}{space 3}0.624{col 79}{space 4}-.1792346{col 92}{space 3}  .297371
{txt}{space 34}21  {c |}{col 39}{res}{space 2} .2109669{col 51}{space 2} .1096468{col 62}{space 1}    1.92{col 71}{space 3}0.057{col 79}{space 4}-.0064668{col 92}{space 3} .4284005
{txt}{space 34}22  {c |}{col 39}{res}{space 2} .1479448{col 51}{space 2} .1736256{col 62}{space 1}    0.85{col 71}{space 3}0.396{col 79}{space 4}-.1963612{col 92}{space 3} .4922508
{txt}{space 34}23  {c |}{col 39}{res}{space 2}-.1045249{col 51}{space 2} .0877022{col 62}{space 1}   -1.19{col 71}{space 3}0.236{col 79}{space 4}-.2784416{col 92}{space 3} .0693917
{txt}{space 34}24  {c |}{col 39}{res}{space 2} .2482074{col 51}{space 2} .1222044{col 62}{space 1}    2.03{col 71}{space 3}0.045{col 79}{space 4} .0058714{col 92}{space 3} .4905433
{txt}{space 34}25  {c |}{col 39}{res}{space 2} .1889249{col 51}{space 2} .1487131{col 62}{space 1}    1.27{col 71}{space 3}0.207{col 79}{space 4}-.1059788{col 92}{space 3} .4838286
{txt}{space 34}26  {c |}{col 39}{res}{space 2} .0513274{col 51}{space 2} .1315907{col 62}{space 1}    0.39{col 71}{space 3}0.697{col 79}{space 4}-.2096218{col 92}{space 3} .3122767
{txt}{space 34}27  {c |}{col 39}{res}{space 2} .3578602{col 51}{space 2} .1969809{col 62}{space 1}    1.82{col 71}{space 3}0.072{col 79}{space 4}-.0327603{col 92}{space 3} .7484807
{txt}{space 34}28  {c |}{col 39}{res}{space 2}-.0500899{col 51}{space 2} .1115213{col 62}{space 1}   -0.45{col 71}{space 3}0.654{col 79}{space 4}-.2712409{col 92}{space 3} .1710611
{txt}{space 34}29  {c |}{col 39}{res}{space 2} .0797353{col 51}{space 2} .1874725{col 62}{space 1}    0.43{col 71}{space 3}0.671{col 79}{space 4}-.2920298{col 92}{space 3} .4515004
{txt}{space 34}30  {c |}{col 39}{res}{space 2} .1611413{col 51}{space 2}  .173413{col 62}{space 1}    0.93{col 71}{space 3}0.355{col 79}{space 4}-.1827432{col 92}{space 3} .5050258
{txt}{space 34}31  {c |}{col 39}{res}{space 2}-.0206525{col 51}{space 2} .1794213{col 62}{space 1}   -0.12{col 71}{space 3}0.909{col 79}{space 4}-.3764517{col 92}{space 3} .3351468
{txt}{space 34}32  {c |}{col 39}{res}{space 2} .2054352{col 51}{space 2} .1422949{col 62}{space 1}    1.44{col 71}{space 3}0.152{col 79}{space 4} -.076741{col 92}{space 3} .4876114
{txt}{space 34}33  {c |}{col 39}{res}{space 2}  .119242{col 51}{space 2} .0895102{col 62}{space 1}    1.33{col 71}{space 3}0.186{col 79}{space 4}-.0582601{col 92}{space 3}  .296744
{txt}{space 34}34  {c |}{col 39}{res}{space 2}  -.14562{col 51}{space 2} .2266747{col 62}{space 1}   -0.64{col 71}{space 3}0.522{col 79}{space 4}-.5951244{col 92}{space 3} .3038844
{txt}{space 34}35  {c |}{col 39}{res}{space 2}  .139722{col 51}{space 2} .1023711{col 62}{space 1}    1.36{col 71}{space 3}0.175{col 79}{space 4}-.0632838{col 92}{space 3} .3427277
{txt}{space 34}36  {c |}{col 39}{res}{space 2} .2127901{col 51}{space 2} .1350436{col 62}{space 1}    1.58{col 71}{space 3}0.118{col 79}{space 4}-.0550064{col 92}{space 3} .4805866
{txt}{space 34}37  {c |}{col 39}{res}{space 2} .1968587{col 51}{space 2} .1149573{col 62}{space 1}    1.71{col 71}{space 3}0.090{col 79}{space 4} -.031106{col 92}{space 3} .4248234
{txt}{space 34}38  {c |}{col 39}{res}{space 2} .3107742{col 51}{space 2} .1960587{col 62}{space 1}    1.59{col 71}{space 3}0.116{col 79}{space 4}-.0780176{col 92}{space 3}  .699566
{txt}{space 34}39  {c |}{col 39}{res}{space 2} .2160492{col 51}{space 2} .1177824{col 62}{space 1}    1.83{col 71}{space 3}0.069{col 79}{space 4}-.0175177{col 92}{space 3} .4496161
{txt}{space 34}40  {c |}{col 39}{res}{space 2} .0428991{col 51}{space 2} .0782035{col 62}{space 1}    0.55{col 71}{space 3}0.584{col 79}{space 4}-.1121813{col 92}{space 3} .1979795
{txt}{space 34}41  {c |}{col 39}{res}{space 2} .1835652{col 51}{space 2} .1716361{col 62}{space 1}    1.07{col 71}{space 3}0.287{col 79}{space 4}-.1567956{col 92}{space 3}  .523926
{txt}{space 34}42  {c |}{col 39}{res}{space 2} .2198068{col 51}{space 2} .1607997{col 62}{space 1}    1.37{col 71}{space 3}0.175{col 79}{space 4}-.0990652{col 92}{space 3} .5386787
{txt}{space 34}43  {c |}{col 39}{res}{space 2} .0063776{col 51}{space 2} .0739026{col 62}{space 1}    0.09{col 71}{space 3}0.931{col 79}{space 4}-.1401741{col 92}{space 3} .1529293
{txt}{space 34}44  {c |}{col 39}{res}{space 2} .2582019{col 51}{space 2} .1371729{col 62}{space 1}    1.88{col 71}{space 3}0.063{col 79}{space 4}-.0138171{col 92}{space 3} .5302209
{txt}{space 34}45  {c |}{col 39}{res}{space 2} .2203259{col 51}{space 2} .1204372{col 62}{space 1}    1.83{col 71}{space 3}0.070{col 79}{space 4}-.0185056{col 92}{space 3} .4591574
{txt}{space 34}46  {c |}{col 39}{res}{space 2} .1298791{col 51}{space 2} .2120377{col 62}{space 1}    0.61{col 71}{space 3}0.542{col 79}{space 4}-.2905997{col 92}{space 3} .5503579
{txt}{space 34}47  {c |}{col 39}{res}{space 2} .1532887{col 51}{space 2} .0925266{col 62}{space 1}    1.66{col 71}{space 3}0.101{col 79}{space 4} -.030195{col 92}{space 3} .3367724
{txt}{space 34}48  {c |}{col 39}{res}{space 2} .2391515{col 51}{space 2} .1889946{col 62}{space 1}    1.27{col 71}{space 3}0.209{col 79}{space 4}-.1356319{col 92}{space 3} .6139348
{txt}{space 34}49  {c |}{col 39}{res}{space 2}  .333178{col 51}{space 2} .2042455{col 62}{space 1}    1.63{col 71}{space 3}0.106{col 79}{space 4}-.0718484{col 92}{space 3} .7382045
{txt}{space 34}50  {c |}{col 39}{res}{space 2} .3450811{col 51}{space 2} .1845717{col 62}{space 1}    1.87{col 71}{space 3}0.064{col 79}{space 4}-.0209314{col 92}{space 3} .7110937
{txt}{space 34}51  {c |}{col 39}{res}{space 2} .3386801{col 51}{space 2} .2316185{col 62}{space 1}    1.46{col 71}{space 3}0.147{col 79}{space 4}-.1206281{col 92}{space 3} .7979882
{txt}{space 34}52  {c |}{col 39}{res}{space 2} .2369124{col 51}{space 2} .2312944{col 62}{space 1}    1.02{col 71}{space 3}0.308{col 79}{space 4}-.2217531{col 92}{space 3}  .695578
{txt}{space 34}53  {c |}{col 39}{res}{space 2} .2728024{col 51}{space 2} .1662856{col 62}{space 1}    1.64{col 71}{space 3}0.104{col 79}{space 4}-.0569482{col 92}{space 3} .6025531
{txt}{space 34}54  {c |}{col 39}{res}{space 2} .2917949{col 51}{space 2} .1841382{col 62}{space 1}    1.58{col 71}{space 3}0.116{col 79}{space 4}-.0733581{col 92}{space 3} .6569479
{txt}{space 34}55  {c |}{col 39}{res}{space 2} .4164944{col 51}{space 2} .2354714{col 62}{space 1}    1.77{col 71}{space 3}0.080{col 79}{space 4}-.0504542{col 92}{space 3} .8834431
{txt}{space 34}56  {c |}{col 39}{res}{space 2} .2477589{col 51}{space 2} .2411244{col 62}{space 1}    1.03{col 71}{space 3}0.307{col 79}{space 4}-.2303999{col 92}{space 3} .7259177
{txt}{space 34}57  {c |}{col 39}{res}{space 2} .3162731{col 51}{space 2} .3041803{col 62}{space 1}    1.04{col 71}{space 3}0.301{col 79}{space 4}-.2869279{col 92}{space 3} .9194742
{txt}{space 34}58  {c |}{col 39}{res}{space 2} .1994914{col 51}{space 2} .1743252{col 62}{space 1}    1.14{col 71}{space 3}0.255{col 79}{space 4}-.1462019{col 92}{space 3} .5451847
{txt}{space 34}59  {c |}{col 39}{res}{space 2} .1973756{col 51}{space 2} .2089574{col 62}{space 1}    0.94{col 71}{space 3}0.347{col 79}{space 4}-.2169948{col 92}{space 3} .6117459
{txt}{space 34}60  {c |}{col 39}{res}{space 2} .1447919{col 51}{space 2} .1035683{col 62}{space 1}    1.40{col 71}{space 3}0.165{col 79}{space 4}-.0605881{col 92}{space 3} .3501718
{txt}{space 34}61  {c |}{col 39}{res}{space 2} .1366978{col 51}{space 2} .1105167{col 62}{space 1}    1.24{col 71}{space 3}0.219{col 79}{space 4} -.082461{col 92}{space 3} .3558566
{txt}{space 34}62  {c |}{col 39}{res}{space 2} .3213231{col 51}{space 2} .2067025{col 62}{space 1}    1.55{col 71}{space 3}0.123{col 79}{space 4}-.0885758{col 92}{space 3}  .731222
{txt}{space 34}63  {c |}{col 39}{res}{space 2} .3904497{col 51}{space 2} .2011296{col 62}{space 1}    1.94{col 71}{space 3}0.055{col 79}{space 4}-.0083979{col 92}{space 3} .7892972
{txt}{space 34}64  {c |}{col 39}{res}{space 2} .4013515{col 51}{space 2} .2109975{col 62}{space 1}    1.90{col 71}{space 3}0.060{col 79}{space 4}-.0170644{col 92}{space 3} .8197675
{txt}{space 34}65  {c |}{col 39}{res}{space 2} .2126162{col 51}{space 2} .1212788{col 62}{space 1}    1.75{col 71}{space 3}0.083{col 79}{space 4}-.0278843{col 92}{space 3} .4531167
{txt}{space 34}66  {c |}{col 39}{res}{space 2} .1925402{col 51}{space 2} .2236025{col 62}{space 1}    0.86{col 71}{space 3}0.391{col 79}{space 4} -.250872{col 92}{space 3} .6359524
{txt}{space 34}67  {c |}{col 39}{res}{space 2} .2234104{col 51}{space 2} .1368904{col 62}{space 1}    1.63{col 71}{space 3}0.106{col 79}{space 4}-.0480485{col 92}{space 3} .4948693
{txt}{space 34}68  {c |}{col 39}{res}{space 2} .2810147{col 51}{space 2} .1525439{col 62}{space 1}    1.84{col 71}{space 3}0.068{col 79}{space 4}-.0214855{col 92}{space 3} .5835149
{txt}{space 34}69  {c |}{col 39}{res}{space 2} .1416401{col 51}{space 2} .1227423{col 62}{space 1}    1.15{col 71}{space 3}0.251{col 79}{space 4}-.1017626{col 92}{space 3} .3850427
{txt}{space 34}70  {c |}{col 39}{res}{space 2}  .350256{col 51}{space 2} .2107735{col 62}{space 1}    1.66{col 71}{space 3}0.100{col 79}{space 4}-.0677159{col 92}{space 3} .7682278
{txt}{space 34}71  {c |}{col 39}{res}{space 2}-.1039501{col 51}{space 2} .1813049{col 62}{space 1}   -0.57{col 71}{space 3}0.568{col 79}{space 4}-.4634845{col 92}{space 3} .2555842
{txt}{space 34}72  {c |}{col 39}{res}{space 2} .2003857{col 51}{space 2} .1185305{col 62}{space 1}    1.69{col 71}{space 3}0.094{col 79}{space 4}-.0346647{col 92}{space 3} .4354361
{txt}{space 34}73  {c |}{col 39}{res}{space 2} .4252965{col 51}{space 2} .1921622{col 62}{space 1}    2.21{col 71}{space 3}0.029{col 79}{space 4} .0442315{col 92}{space 3} .8063614
{txt}{space 34}74  {c |}{col 39}{res}{space 2} .1516712{col 51}{space 2} .1023696{col 62}{space 1}    1.48{col 71}{space 3}0.141{col 79}{space 4}-.0513315{col 92}{space 3}  .354674
{txt}{space 34}75  {c |}{col 39}{res}{space 2} .0702328{col 51}{space 2} .1503103{col 62}{space 1}    0.47{col 71}{space 3}0.641{col 79}{space 4}-.2278381{col 92}{space 3} .3683037
{txt}{space 34}76  {c |}{col 39}{res}{space 2} .2948962{col 51}{space 2} .1726546{col 62}{space 1}    1.71{col 71}{space 3}0.091{col 79}{space 4}-.0474843{col 92}{space 3} .6372767
{txt}{space 34}77  {c |}{col 39}{res}{space 2} .2211507{col 51}{space 2} .1711861{col 62}{space 1}    1.29{col 71}{space 3}0.199{col 79}{space 4}-.1183178{col 92}{space 3} .5606192
{txt}{space 34}78  {c |}{col 39}{res}{space 2} .2695141{col 51}{space 2} .1094133{col 62}{space 1}    2.46{col 71}{space 3}0.015{col 79}{space 4} .0525434{col 92}{space 3} .4864848
{txt}{space 34}79  {c |}{col 39}{res}{space 2}-.0170673{col 51}{space 2} .0254471{col 62}{space 1}   -0.67{col 71}{space 3}0.504{col 79}{space 4}-.0675299{col 92}{space 3} .0333953
{txt}{space 34}80  {c |}{col 39}{res}{space 2} .4341768{col 51}{space 2} .2175748{col 62}{space 1}    2.00{col 71}{space 3}0.049{col 79}{space 4} .0027177{col 92}{space 3} .8656358
{txt}{space 34}81  {c |}{col 39}{res}{space 2} .1566748{col 51}{space 2} .2383508{col 62}{space 1}    0.66{col 71}{space 3}0.512{col 79}{space 4}-.3159837{col 92}{space 3} .6293333
{txt}{space 34}82  {c |}{col 39}{res}{space 2} .2357782{col 51}{space 2} .2041584{col 62}{space 1}    1.15{col 71}{space 3}0.251{col 79}{space 4}-.1690757{col 92}{space 3}  .640632
{txt}{space 34}83  {c |}{col 39}{res}{space 2} .3443791{col 51}{space 2} .1690467{col 62}{space 1}    2.04{col 71}{space 3}0.044{col 79}{space 4} .0091532{col 92}{space 3}  .679605
{txt}{space 34}84  {c |}{col 39}{res}{space 2} .2872119{col 51}{space 2} .2072255{col 62}{space 1}    1.39{col 71}{space 3}0.169{col 79}{space 4}-.1237239{col 92}{space 3} .6981478
{txt}{space 34}85  {c |}{col 39}{res}{space 2} .3047585{col 51}{space 2} .1612251{col 62}{space 1}    1.89{col 71}{space 3}0.062{col 79}{space 4}-.0149568{col 92}{space 3} .6244738
{txt}{space 34}86  {c |}{col 39}{res}{space 2} .3295317{col 51}{space 2}  .240108{col 62}{space 1}    1.37{col 71}{space 3}0.173{col 79}{space 4}-.1466115{col 92}{space 3}  .805675
{txt}{space 34}87  {c |}{col 39}{res}{space 2} .3849397{col 51}{space 2} .2401566{col 62}{space 1}    1.60{col 71}{space 3}0.112{col 79}{space 4}-.0912998{col 92}{space 3} .8611792
{txt}{space 34}88  {c |}{col 39}{res}{space 2} .1702313{col 51}{space 2} .1688896{col 62}{space 1}    1.01{col 71}{space 3}0.316{col 79}{space 4}-.1646831{col 92}{space 3} .5051456
{txt}{space 34}89  {c |}{col 39}{res}{space 2} .2296674{col 51}{space 2} .1642975{col 62}{space 1}    1.40{col 71}{space 3}0.165{col 79}{space 4}-.0961407{col 92}{space 3} .5554756
{txt}{space 34}90  {c |}{col 39}{res}{space 2} .0212664{col 51}{space 2} .0838105{col 62}{space 1}    0.25{col 71}{space 3}0.800{col 79}{space 4}-.1449329{col 92}{space 3} .1874658
{txt}{space 34}91  {c |}{col 39}{res}{space 2}  .141594{col 51}{space 2}  .118141{col 62}{space 1}    1.20{col 71}{space 3}0.233{col 79}{space 4}-.0926841{col 92}{space 3} .3758721
{txt}{space 34}92  {c |}{col 39}{res}{space 2} .0818275{col 51}{space 2}  .059768{col 62}{space 1}    1.37{col 71}{space 3}0.174{col 79}{space 4}-.0366946{col 92}{space 3} .2003497
{txt}{space 34}93  {c |}{col 39}{res}{space 2} .3546497{col 51}{space 2} .1729696{col 62}{space 1}    2.05{col 71}{space 3}0.043{col 79}{space 4} .0116446{col 92}{space 3} .6976548
{txt}{space 34}94  {c |}{col 39}{res}{space 2} .4515512{col 51}{space 2} .2120943{col 62}{space 1}    2.13{col 71}{space 3}0.036{col 79}{space 4} .0309603{col 92}{space 3} .8721421
{txt}{space 34}95  {c |}{col 39}{res}{space 2} .1699187{col 51}{space 2} .2081395{col 62}{space 1}    0.82{col 71}{space 3}0.416{col 79}{space 4}-.2428298{col 92}{space 3} .5826672
{txt}{space 34}96  {c |}{col 39}{res}{space 2}  .295172{col 51}{space 2} .1882488{col 62}{space 1}    1.57{col 71}{space 3}0.120{col 79}{space 4}-.0781324{col 92}{space 3} .6684763
{txt}{space 34}97  {c |}{col 39}{res}{space 2} .3311656{col 51}{space 2} .1539413{col 62}{space 1}    2.15{col 71}{space 3}0.034{col 79}{space 4} .0258942{col 92}{space 3}  .636437
{txt}{space 34}98  {c |}{col 39}{res}{space 2} .4432233{col 51}{space 2} .2215224{col 62}{space 1}    2.00{col 71}{space 3}0.048{col 79}{space 4} .0039361{col 92}{space 3} .8825106
{txt}{space 34}99  {c |}{col 39}{res}{space 2} .0447567{col 51}{space 2} .0559925{col 62}{space 1}    0.80{col 71}{space 3}0.426{col 79}{space 4}-.0662784{col 92}{space 3} .1557919
{txt}{space 33}100  {c |}{col 39}{res}{space 2}  .209541{col 51}{space 2} .2102733{col 62}{space 1}    1.00{col 71}{space 3}0.321{col 79}{space 4} -.207439{col 92}{space 3} .6265209
{txt}{space 33}101  {c |}{col 39}{res}{space 2} .3679877{col 51}{space 2} .1666023{col 62}{space 1}    2.21{col 71}{space 3}0.029{col 79}{space 4} .0376091{col 92}{space 3} .6983663
{txt}{space 33}102  {c |}{col 39}{res}{space 2} .2778898{col 51}{space 2} .2137078{col 62}{space 1}    1.30{col 71}{space 3}0.196{col 79}{space 4}-.1459007{col 92}{space 3} .7016804
{txt}{space 33}103  {c |}{col 39}{res}{space 2} .0801864{col 51}{space 2} .1172537{col 62}{space 1}    0.68{col 71}{space 3}0.496{col 79}{space 4}-.1523321{col 92}{space 3} .3127049
{txt}{space 33}104  {c |}{col 39}{res}{space 2}-.1597412{col 51}{space 2}  .060443{col 62}{space 1}   -2.64{col 71}{space 3}0.009{col 79}{space 4}-.2796021{col 92}{space 3}-.0398804
{txt}{space 33}105  {c |}{col 39}{res}{space 2} .2288614{col 51}{space 2} .1993324{col 62}{space 1}    1.15{col 71}{space 3}0.254{col 79}{space 4}-.1664223{col 92}{space 3}  .624145
{txt}{space 37} {c |}
{space 33}year {c |}
{space 32}2011  {c |}{col 39}{res}{space 2}-.0023514{col 51}{space 2} .0037683{col 62}{space 1}   -0.62{col 71}{space 3}0.534{col 79}{space 4} -.009824{col 92}{space 3} .0051212
{txt}{space 32}2012  {c |}{col 39}{res}{space 2} .0046028{col 51}{space 2} .0045064{col 62}{space 1}    1.02{col 71}{space 3}0.309{col 79}{space 4}-.0043335{col 92}{space 3} .0135392
{txt}{space 32}2013  {c |}{col 39}{res}{space 2} .0026863{col 51}{space 2} .0056061{col 62}{space 1}    0.48{col 71}{space 3}0.633{col 79}{space 4}-.0084309{col 92}{space 3} .0138034
{txt}{space 32}2014  {c |}{col 39}{res}{space 2}-.0023693{col 51}{space 2} .0065794{col 62}{space 1}   -0.36{col 71}{space 3}0.719{col 79}{space 4}-.0154166{col 92}{space 3}  .010678
{txt}{space 32}2015  {c |}{col 39}{res}{space 2}-.0102153{col 51}{space 2} .0079866{col 62}{space 1}   -1.28{col 71}{space 3}0.204{col 79}{space 4} -.026053{col 92}{space 3} .0056223
{txt}{space 32}2016  {c |}{col 39}{res}{space 2}-.0132289{col 51}{space 2} .0079652{col 62}{space 1}   -1.66{col 71}{space 3}0.100{col 79}{space 4}-.0290241{col 92}{space 3} .0025664
{txt}{space 32}2017  {c |}{col 39}{res}{space 2}-.0029207{col 51}{space 2} .0117917{col 62}{space 1}   -0.25{col 71}{space 3}0.805{col 79}{space 4} -.026304{col 92}{space 3} .0204626
{txt}{space 32}2018  {c |}{col 39}{res}{space 2}-.0293206{col 51}{space 2} .0107094{col 62}{space 1}   -2.74{col 71}{space 3}0.007{col 79}{space 4}-.0505577{col 92}{space 3}-.0080835
{txt}{space 32}2019  {c |}{col 39}{res}{space 2}-.0684656{col 51}{space 2} .0120915{col 62}{space 1}   -5.66{col 71}{space 3}0.000{col 79}{space 4}-.0924434{col 92}{space 3}-.0444877
{txt}{space 37} {c |}
{space 32}_cons {c |}{col 39}{res}{space 2} .0390471{col 51}{space 2} .5065088{col 62}{space 1}    0.08{col 71}{space 3}0.939{col 79}{space 4} -.965379{col 92}{space 3} 1.043473
{txt}{hline 38}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891132{col 50}    20{col 58}  3782304{col 69}  3782559
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0535774{col 26}{space 2} .0340399{col 37}{space 1}    1.57{col 46}{space 3}0.119{col 54}{space 4}-.0139249{col 67}{space 3} .1210798
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0270159{col 26}{space 2} .0151078{col 37}{space 1}    1.79{col 46}{space 3}0.077{col 54}{space 4}-.0029434{col 67}{space 3} .0569753
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0543246{col 26}{space 2} .0185932{col 37}{space 1}    2.92{col 46}{space 3}0.004{col 54}{space 4} .0174537{col 67}{space 3} .0911956
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub -  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0273087{col 26}{space 2}  .013118{col 37}{space 1}    2.08{col 46}{space 3}0.040{col 54}{space 4} .0012953{col 67}{space 3} .0533221
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
.    
. *** 4. TABLE A1 [MODELS 5-8]: CONDITIONAL-RESPONDENT MODELS EVALUATING THE RELATIONSHIP INVOLVING WITHIN-IDENTITY "OUT-GROUP" STATUS & BETWEEN-IDENTITY GROUP STATUS DIFFERENTIALS AS A MEANS TO FOSTER DIVERSITY AND INCLUSION IN THE U.S. CIVILIAN WORKFORCE [BY NON-SUPERVISORS POSITIONS VERSUS SUPERVISORY POSITION] ***   
. 
. 
. 
. 
. 
.    
. *** MODEL 5: CONDITIONAL RESPONSES BY GENDER & POSITION --  GENDER WITHIN-IDENTITY 'OUT-GROUP' STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.gender##i.supervisor    ln_ratio_fem_tot_men_tot   minority  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0405
                                                {txt}Root MSE          =    {res} .51451

{txt}{ralign 106:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 41}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 42}{c |}{col 54}    Robust
{col 1}                     lndiversity2zeroadj{col 42}{c |} Coefficient{col 54}  std. err.{col 66}      t{col 74}   P>|t|{col 82}     [95% con{col 95}f. interval]
{hline 41}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 20}ln_ratio_fmsup_fmsub {c |}{col 42}{res}{space 2} .1368125{col 54}{space 2} .0448884{col 65}{space 1}    3.05{col 74}{space 3}0.003{col 82}{space 4} .0477971{col 95}{space 3}  .225828
{txt}{space 32}1.gender {c |}{col 42}{res}{space 2}-.0389746{col 54}{space 2} .0099862{col 65}{space 1}   -3.90{col 74}{space 3}0.000{col 82}{space 4}-.0587775{col 95}{space 3}-.0191717
{txt}{space 40} {c |}
{space 11}gender#c.ln_ratio_fmsup_fmsub {c |}
{space 38}1  {c |}{col 42}{res}{space 2} .0075368{col 54}{space 2} .0262953{col 65}{space 1}    0.29{col 74}{space 3}0.775{col 82}{space 4}-.0446076{col 95}{space 3} .0596813
{txt}{space 40} {c |}
{space 28}1.supervisor {c |}{col 42}{res}{space 2} .1446413{col 54}{space 2} .0210212{col 65}{space 1}    6.88{col 74}{space 3}0.000{col 82}{space 4} .1029554{col 95}{space 3} .1863271
{txt}{space 40} {c |}
{space 7}supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 38}1  {c |}{col 42}{res}{space 2} .0574054{col 54}{space 2}  .042089{col 65}{space 1}    1.36{col 74}{space 3}0.176{col 82}{space 4}-.0260586{col 95}{space 3} .1408695
{txt}{space 40} {c |}
{space 23}gender#supervisor {c |}
{space 36}1 1  {c |}{col 42}{res}{space 2} .0057964{col 54}{space 2} .0146361{col 65}{space 1}    0.40{col 74}{space 3}0.693{col 82}{space 4}-.0232274{col 95}{space 3} .0348203
{txt}{space 40} {c |}
gender#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 36}1 1  {c |}{col 42}{res}{space 2}-.0059445{col 54}{space 2} .0297715{col 65}{space 1}   -0.20{col 74}{space 3}0.842{col 82}{space 4}-.0649825{col 95}{space 3} .0530936
{txt}{space 40} {c |}
{space 16}ln_ratio_fem_tot_men_tot {c |}{col 42}{res}{space 2}-.0066033{col 54}{space 2} .0553907{col 65}{space 1}   -0.12{col 74}{space 3}0.905{col 82}{space 4}-.1164451{col 95}{space 3} .1032386
{txt}{space 32}minority {c |}{col 42}{res}{space 2}-.0944347{col 54}{space 2} .0037778{col 65}{space 1}  -25.00{col 74}{space 3}0.000{col 82}{space 4}-.1019262{col 95}{space 3}-.0869431
{txt}{space 26}topoffgender_2 {c |}{col 42}{res}{space 2}-.0028141{col 54}{space 2} .0044966{col 65}{space 1}   -0.63{col 74}{space 3}0.533{col 82}{space 4}-.0117311{col 95}{space 3} .0061029
{txt}{space 20}lntotworkforce_count {c |}{col 42}{res}{space 2} .0764533{col 54}{space 2} .0321443{col 65}{space 1}    2.38{col 74}{space 3}0.019{col 82}{space 4} .0127098{col 95}{space 3} .1401967
{txt}{space 12}ln_professionals_total_ratio {c |}{col 42}{res}{space 2}   .00738{col 54}{space 2} .0412033{col 65}{space 1}    0.18{col 74}{space 3}0.858{col 82}{space 4}-.0743276{col 95}{space 3} .0890876
{txt}{space 40} {c |}
{space 32}agencyid {c |}
{space 38}2  {c |}{col 42}{res}{space 2}  .316128{col 54}{space 2} .1135817{col 65}{space 1}    2.78{col 74}{space 3}0.006{col 82}{space 4} .0908912{col 95}{space 3} .5413648
{txt}{space 38}3  {c |}{col 42}{res}{space 2} .0951506{col 54}{space 2} .0536355{col 65}{space 1}    1.77{col 74}{space 3}0.079{col 82}{space 4}-.0112105{col 95}{space 3} .2015118
{txt}{space 38}4  {c |}{col 42}{res}{space 2} .4442106{col 54}{space 2} .1491548{col 65}{space 1}    2.98{col 74}{space 3}0.004{col 82}{space 4} .1484309{col 95}{space 3} .7399903
{txt}{space 38}5  {c |}{col 42}{res}{space 2} .2675067{col 54}{space 2} .1036577{col 65}{space 1}    2.58{col 74}{space 3}0.011{col 82}{space 4} .0619495{col 95}{space 3} .4730638
{txt}{space 38}6  {c |}{col 42}{res}{space 2} .2534119{col 54}{space 2} .1100051{col 65}{space 1}    2.30{col 74}{space 3}0.023{col 82}{space 4} .0352676{col 95}{space 3} .4715562
{txt}{space 38}7  {c |}{col 42}{res}{space 2}  .362466{col 54}{space 2} .1814578{col 65}{space 1}    2.00{col 74}{space 3}0.048{col 82}{space 4} .0026284{col 95}{space 3} .7223035
{txt}{space 38}8  {c |}{col 42}{res}{space 2} .3075415{col 54}{space 2} .1417851{col 65}{space 1}    2.17{col 74}{space 3}0.032{col 82}{space 4} .0263763{col 95}{space 3} .5887067
{txt}{space 38}9  {c |}{col 42}{res}{space 2}  -.01183{col 54}{space 2} .0227245{col 65}{space 1}   -0.52{col 74}{space 3}0.604{col 82}{space 4}-.0568935{col 95}{space 3} .0332336
{txt}{space 37}10  {c |}{col 42}{res}{space 2} .2558811{col 54}{space 2} .1600381{col 65}{space 1}    1.60{col 74}{space 3}0.113{col 82}{space 4}-.0614804{col 95}{space 3} .5732426
{txt}{space 37}11  {c |}{col 42}{res}{space 2} .2174247{col 54}{space 2} .1175293{col 65}{space 1}    1.85{col 74}{space 3}0.067{col 82}{space 4}-.0156404{col 95}{space 3} .4504898
{txt}{space 37}12  {c |}{col 42}{res}{space 2} .3812814{col 54}{space 2} .1694332{col 65}{space 1}    2.25{col 74}{space 3}0.027{col 82}{space 4}  .045289{col 95}{space 3} .7172738
{txt}{space 37}13  {c |}{col 42}{res}{space 2} .3625306{col 54}{space 2} .1428215{col 65}{space 1}    2.54{col 74}{space 3}0.013{col 82}{space 4} .0793103{col 95}{space 3} .6457509
{txt}{space 37}14  {c |}{col 42}{res}{space 2} .1653824{col 54}{space 2} .1050729{col 65}{space 1}    1.57{col 74}{space 3}0.119{col 82}{space 4}-.0429811{col 95}{space 3} .3737459
{txt}{space 37}15  {c |}{col 42}{res}{space 2} .3074754{col 54}{space 2} .1158608{col 65}{space 1}    2.65{col 74}{space 3}0.009{col 82}{space 4} .0777192{col 95}{space 3} .5372317
{txt}{space 37}16  {c |}{col 42}{res}{space 2} .4785613{col 54}{space 2} .1961068{col 65}{space 1}    2.44{col 74}{space 3}0.016{col 82}{space 4} .0896742{col 95}{space 3} .8674484
{txt}{space 37}17  {c |}{col 42}{res}{space 2} .1351137{col 54}{space 2} .1559217{col 65}{space 1}    0.87{col 74}{space 3}0.388{col 82}{space 4}-.1740848{col 95}{space 3} .4443122
{txt}{space 37}18  {c |}{col 42}{res}{space 2} .3608879{col 54}{space 2}  .152061{col 65}{space 1}    2.37{col 74}{space 3}0.019{col 82}{space 4} .0593452{col 95}{space 3} .6624306
{txt}{space 37}19  {c |}{col 42}{res}{space 2} .2263686{col 54}{space 2} .0980805{col 65}{space 1}    2.31{col 74}{space 3}0.023{col 82}{space 4} .0318714{col 95}{space 3} .4208659
{txt}{space 37}20  {c |}{col 42}{res}{space 2} .3080917{col 54}{space 2} .1582249{col 65}{space 1}    1.95{col 74}{space 3}0.054{col 82}{space 4}-.0056742{col 95}{space 3} .6218576
{txt}{space 37}21  {c |}{col 42}{res}{space 2} .2737085{col 54}{space 2}   .11858{col 65}{space 1}    2.31{col 74}{space 3}0.023{col 82}{space 4}   .03856{col 95}{space 3} .5088571
{txt}{space 37}22  {c |}{col 42}{res}{space 2}  .274905{col 54}{space 2} .1428832{col 65}{space 1}    1.92{col 74}{space 3}0.057{col 82}{space 4}-.0084377{col 95}{space 3} .5582478
{txt}{space 37}23  {c |}{col 42}{res}{space 2} -.083988{col 54}{space 2} .0510709{col 65}{space 1}   -1.64{col 74}{space 3}0.103{col 82}{space 4}-.1852635{col 95}{space 3} .0172874
{txt}{space 37}24  {c |}{col 42}{res}{space 2} .2972384{col 54}{space 2} .0953838{col 65}{space 1}    3.12{col 74}{space 3}0.002{col 82}{space 4} .1080888{col 95}{space 3}  .486388
{txt}{space 37}25  {c |}{col 42}{res}{space 2} .2002326{col 54}{space 2} .1342538{col 65}{space 1}    1.49{col 74}{space 3}0.139{col 82}{space 4}-.0659978{col 95}{space 3} .4664629
{txt}{space 37}26  {c |}{col 42}{res}{space 2} .1064877{col 54}{space 2} .1098238{col 65}{space 1}    0.97{col 74}{space 3}0.334{col 82}{space 4} -.111297{col 95}{space 3} .3242723
{txt}{space 37}27  {c |}{col 42}{res}{space 2} .3936152{col 54}{space 2}  .156644{col 65}{space 1}    2.51{col 74}{space 3}0.014{col 82}{space 4} .0829842{col 95}{space 3} .7042462
{txt}{space 37}28  {c |}{col 42}{res}{space 2}  .007117{col 54}{space 2} .0721811{col 65}{space 1}    0.10{col 74}{space 3}0.922{col 82}{space 4}-.1360208{col 95}{space 3} .1502547
{txt}{space 37}29  {c |}{col 42}{res}{space 2} .1136071{col 54}{space 2} .1297594{col 65}{space 1}    0.88{col 74}{space 3}0.383{col 82}{space 4}-.1437105{col 95}{space 3} .3709248
{txt}{space 37}30  {c |}{col 42}{res}{space 2} .1459723{col 54}{space 2} .1209251{col 65}{space 1}    1.21{col 74}{space 3}0.230{col 82}{space 4}-.0938268{col 95}{space 3} .3857714
{txt}{space 37}31  {c |}{col 42}{res}{space 2}-.0115286{col 54}{space 2} .1446759{col 65}{space 1}   -0.08{col 74}{space 3}0.937{col 82}{space 4}-.2984263{col 95}{space 3} .2753691
{txt}{space 37}32  {c |}{col 42}{res}{space 2} .2560698{col 54}{space 2} .1124463{col 65}{space 1}    2.28{col 74}{space 3}0.025{col 82}{space 4} .0330846{col 95}{space 3} .4790549
{txt}{space 37}33  {c |}{col 42}{res}{space 2} .1544696{col 54}{space 2} .0688083{col 65}{space 1}    2.24{col 74}{space 3}0.027{col 82}{space 4} .0180202{col 95}{space 3}  .290919
{txt}{space 37}34  {c |}{col 42}{res}{space 2} .1546458{col 54}{space 2} .1193533{col 65}{space 1}    1.30{col 74}{space 3}0.198{col 82}{space 4}-.0820362{col 95}{space 3} .3913279
{txt}{space 37}35  {c |}{col 42}{res}{space 2} .1910263{col 54}{space 2} .0933289{col 65}{space 1}    2.05{col 74}{space 3}0.043{col 82}{space 4} .0059516{col 95}{space 3}  .376101
{txt}{space 37}36  {c |}{col 42}{res}{space 2} .2484729{col 54}{space 2} .1172902{col 65}{space 1}    2.12{col 74}{space 3}0.037{col 82}{space 4}  .015882{col 95}{space 3} .4810639
{txt}{space 37}37  {c |}{col 42}{res}{space 2}  .245511{col 54}{space 2}  .111034{col 65}{space 1}    2.21{col 74}{space 3}0.029{col 82}{space 4} .0253265{col 95}{space 3} .4656956
{txt}{space 37}38  {c |}{col 42}{res}{space 2} .3953391{col 54}{space 2} .1623216{col 65}{space 1}    2.44{col 74}{space 3}0.017{col 82}{space 4} .0734493{col 95}{space 3}  .717229
{txt}{space 37}39  {c |}{col 42}{res}{space 2} .2197764{col 54}{space 2}  .115011{col 65}{space 1}    1.91{col 74}{space 3}0.059{col 82}{space 4}-.0082947{col 95}{space 3} .4478475
{txt}{space 37}40  {c |}{col 42}{res}{space 2} .0322701{col 54}{space 2} .0716425{col 65}{space 1}    0.45{col 74}{space 3}0.653{col 82}{space 4}-.1097997{col 95}{space 3}   .17434
{txt}{space 37}41  {c |}{col 42}{res}{space 2} .3099198{col 54}{space 2} .1468633{col 65}{space 1}    2.11{col 74}{space 3}0.037{col 82}{space 4} .0186844{col 95}{space 3} .6011552
{txt}{space 37}42  {c |}{col 42}{res}{space 2} .3217017{col 54}{space 2} .1207971{col 65}{space 1}    2.66{col 74}{space 3}0.009{col 82}{space 4} .0821566{col 95}{space 3} .5612468
{txt}{space 37}43  {c |}{col 42}{res}{space 2} .1088518{col 54}{space 2} .0470079{col 65}{space 1}    2.32{col 74}{space 3}0.023{col 82}{space 4} .0156334{col 95}{space 3} .2020703
{txt}{space 37}44  {c |}{col 42}{res}{space 2} .3571847{col 54}{space 2} .1019521{col 65}{space 1}    3.50{col 74}{space 3}0.001{col 82}{space 4} .1550099{col 95}{space 3} .5593595
{txt}{space 37}45  {c |}{col 42}{res}{space 2} .3070058{col 54}{space 2} .1225672{col 65}{space 1}    2.50{col 74}{space 3}0.014{col 82}{space 4} .0639504{col 95}{space 3} .5500611
{txt}{space 37}46  {c |}{col 42}{res}{space 2} .2890271{col 54}{space 2}  .186688{col 65}{space 1}    1.55{col 74}{space 3}0.125{col 82}{space 4}-.0811823{col 95}{space 3} .6592365
{txt}{space 37}47  {c |}{col 42}{res}{space 2} .2070608{col 54}{space 2} .0854803{col 65}{space 1}    2.42{col 74}{space 3}0.017{col 82}{space 4} .0375502{col 95}{space 3} .3765714
{txt}{space 37}48  {c |}{col 42}{res}{space 2} .2333276{col 54}{space 2} .1326162{col 65}{space 1}    1.76{col 74}{space 3}0.081{col 82}{space 4}-.0296553{col 95}{space 3} .4963105
{txt}{space 37}49  {c |}{col 42}{res}{space 2} .4524006{col 54}{space 2}  .190836{col 65}{space 1}    2.37{col 74}{space 3}0.020{col 82}{space 4} .0739656{col 95}{space 3} .8308356
{txt}{space 37}50  {c |}{col 42}{res}{space 2} .4275647{col 54}{space 2} .1587247{col 65}{space 1}    2.69{col 74}{space 3}0.008{col 82}{space 4} .1128077{col 95}{space 3} .7423218
{txt}{space 37}51  {c |}{col 42}{res}{space 2} .3803592{col 54}{space 2} .1890559{col 65}{space 1}    2.01{col 74}{space 3}0.047{col 82}{space 4} .0054543{col 95}{space 3} .7552641
{txt}{space 37}52  {c |}{col 42}{res}{space 2} .3428647{col 54}{space 2} .1810624{col 65}{space 1}    1.89{col 74}{space 3}0.061{col 82}{space 4}-.0161889{col 95}{space 3} .7019183
{txt}{space 37}53  {c |}{col 42}{res}{space 2} .3051994{col 54}{space 2} .1343832{col 65}{space 1}    2.27{col 74}{space 3}0.025{col 82}{space 4} .0387124{col 95}{space 3} .5716864
{txt}{space 37}54  {c |}{col 42}{res}{space 2}  .348885{col 54}{space 2} .1523057{col 65}{space 1}    2.29{col 74}{space 3}0.024{col 82}{space 4} .0468572{col 95}{space 3} .6509129
{txt}{space 37}55  {c |}{col 42}{res}{space 2} .5451302{col 54}{space 2} .2123155{col 65}{space 1}    2.57{col 74}{space 3}0.012{col 82}{space 4} .1241007{col 95}{space 3} .9661598
{txt}{space 37}56  {c |}{col 42}{res}{space 2} .3046285{col 54}{space 2} .1978474{col 65}{space 1}    1.54{col 74}{space 3}0.127{col 82}{space 4}-.0877104{col 95}{space 3} .6969673
{txt}{space 37}57  {c |}{col 42}{res}{space 2} .4105957{col 54}{space 2} .2284719{col 65}{space 1}    1.80{col 74}{space 3}0.075{col 82}{space 4}-.0424726{col 95}{space 3}  .863664
{txt}{space 37}58  {c |}{col 42}{res}{space 2} .3016679{col 54}{space 2} .1502075{col 65}{space 1}    2.01{col 74}{space 3}0.047{col 82}{space 4} .0038007{col 95}{space 3} .5995351
{txt}{space 37}59  {c |}{col 42}{res}{space 2} .3443365{col 54}{space 2} .1698696{col 65}{space 1}    2.03{col 74}{space 3}0.045{col 82}{space 4} .0074787{col 95}{space 3} .6811943
{txt}{space 37}60  {c |}{col 42}{res}{space 2} .1856614{col 54}{space 2} .0929348{col 65}{space 1}    2.00{col 74}{space 3}0.048{col 82}{space 4} .0013682{col 95}{space 3} .3699546
{txt}{space 37}61  {c |}{col 42}{res}{space 2} .1893811{col 54}{space 2} .1062178{col 65}{space 1}    1.78{col 74}{space 3}0.078{col 82}{space 4}-.0212528{col 95}{space 3}  .400015
{txt}{space 37}62  {c |}{col 42}{res}{space 2} .4015712{col 54}{space 2} .1722455{col 65}{space 1}    2.33{col 74}{space 3}0.022{col 82}{space 4} .0600018{col 95}{space 3} .7431405
{txt}{space 37}63  {c |}{col 42}{res}{space 2} .4629689{col 54}{space 2} .1703766{col 65}{space 1}    2.72{col 74}{space 3}0.008{col 82}{space 4} .1251057{col 95}{space 3}  .800832
{txt}{space 37}64  {c |}{col 42}{res}{space 2} .4659309{col 54}{space 2} .1855408{col 65}{space 1}    2.51{col 74}{space 3}0.014{col 82}{space 4} .0979966{col 95}{space 3} .8338652
{txt}{space 37}65  {c |}{col 42}{res}{space 2}   .27524{col 54}{space 2} .1022267{col 65}{space 1}    2.69{col 74}{space 3}0.008{col 82}{space 4} .0725207{col 95}{space 3} .4779593
{txt}{space 37}66  {c |}{col 42}{res}{space 2} .3289215{col 54}{space 2} .2029218{col 65}{space 1}    1.62{col 74}{space 3}0.108{col 82}{space 4}-.0734802{col 95}{space 3} .7313231
{txt}{space 37}67  {c |}{col 42}{res}{space 2} .3327188{col 54}{space 2}  .131432{col 65}{space 1}    2.53{col 74}{space 3}0.013{col 82}{space 4} .0720842{col 95}{space 3} .5933534
{txt}{space 37}68  {c |}{col 42}{res}{space 2} .3215247{col 54}{space 2} .1482183{col 65}{space 1}    2.17{col 74}{space 3}0.032{col 82}{space 4} .0276021{col 95}{space 3} .6154472
{txt}{space 37}69  {c |}{col 42}{res}{space 2} .1991259{col 54}{space 2} .1138056{col 65}{space 1}    1.75{col 74}{space 3}0.083{col 82}{space 4}-.0265548{col 95}{space 3} .4248066
{txt}{space 37}70  {c |}{col 42}{res}{space 2} .4181046{col 54}{space 2} .1858248{col 65}{space 1}    2.25{col 74}{space 3}0.027{col 82}{space 4}  .049607{col 95}{space 3} .7866023
{txt}{space 37}71  {c |}{col 42}{res}{space 2} .1199539{col 54}{space 2} .1371393{col 65}{space 1}    0.87{col 74}{space 3}0.384{col 82}{space 4}-.1519984{col 95}{space 3} .3919063
{txt}{space 37}72  {c |}{col 42}{res}{space 2} .2795759{col 54}{space 2} .1115795{col 65}{space 1}    2.51{col 74}{space 3}0.014{col 82}{space 4} .0583095{col 95}{space 3} .5008423
{txt}{space 37}73  {c |}{col 42}{res}{space 2} .4982785{col 54}{space 2}  .167893{col 65}{space 1}    2.97{col 74}{space 3}0.004{col 82}{space 4} .1653403{col 95}{space 3} .8312166
{txt}{space 37}74  {c |}{col 42}{res}{space 2} .0995333{col 54}{space 2} .1079523{col 65}{space 1}    0.92{col 74}{space 3}0.359{col 82}{space 4}-.1145401{col 95}{space 3} .3136067
{txt}{space 37}75  {c |}{col 42}{res}{space 2} .1959487{col 54}{space 2} .1271202{col 65}{space 1}    1.54{col 74}{space 3}0.126{col 82}{space 4}-.0561353{col 95}{space 3} .4480328
{txt}{space 37}76  {c |}{col 42}{res}{space 2} .3403763{col 54}{space 2} .1526983{col 65}{space 1}    2.23{col 74}{space 3}0.028{col 82}{space 4} .0375699{col 95}{space 3} .6431826
{txt}{space 37}77  {c |}{col 42}{res}{space 2} .2705615{col 54}{space 2} .1448186{col 65}{space 1}    1.87{col 74}{space 3}0.065{col 82}{space 4}-.0166192{col 95}{space 3} .5577422
{txt}{space 37}78  {c |}{col 42}{res}{space 2} .2994206{col 54}{space 2} .0983211{col 65}{space 1}    3.05{col 74}{space 3}0.003{col 82}{space 4} .1044462{col 95}{space 3} .4943949
{txt}{space 37}79  {c |}{col 42}{res}{space 2}-.0135496{col 54}{space 2} .0162896{col 65}{space 1}   -0.83{col 74}{space 3}0.407{col 82}{space 4}-.0458525{col 95}{space 3} .0187534
{txt}{space 37}80  {c |}{col 42}{res}{space 2} .4405384{col 54}{space 2}  .171513{col 65}{space 1}    2.57{col 74}{space 3}0.012{col 82}{space 4} .1004218{col 95}{space 3} .7806551
{txt}{space 37}81  {c |}{col 42}{res}{space 2} .2260208{col 54}{space 2} .1763747{col 65}{space 1}    1.28{col 74}{space 3}0.203{col 82}{space 4}-.1237369{col 95}{space 3} .5757785
{txt}{space 37}82  {c |}{col 42}{res}{space 2}  .362393{col 54}{space 2} .1835024{col 65}{space 1}    1.97{col 74}{space 3}0.051{col 82}{space 4}-.0014992{col 95}{space 3} .7262852
{txt}{space 37}83  {c |}{col 42}{res}{space 2} .4345875{col 54}{space 2} .1445021{col 65}{space 1}    3.01{col 74}{space 3}0.003{col 82}{space 4} .1480343{col 95}{space 3} .7211407
{txt}{space 37}84  {c |}{col 42}{res}{space 2} .3392793{col 54}{space 2} .1838654{col 65}{space 1}    1.85{col 74}{space 3}0.068{col 82}{space 4}-.0253327{col 95}{space 3} .7038912
{txt}{space 37}85  {c |}{col 42}{res}{space 2}  .410313{col 54}{space 2} .1460119{col 65}{space 1}    2.81{col 74}{space 3}0.006{col 82}{space 4} .1207659{col 95}{space 3} .6998601
{txt}{space 37}86  {c |}{col 42}{res}{space 2} .4689809{col 54}{space 2} .1887108{col 65}{space 1}    2.49{col 74}{space 3}0.015{col 82}{space 4} .0947603{col 95}{space 3} .8432014
{txt}{space 37}87  {c |}{col 42}{res}{space 2}  .472359{col 54}{space 2} .1894345{col 65}{space 1}    2.49{col 74}{space 3}0.014{col 82}{space 4} .0967033{col 95}{space 3} .8480147
{txt}{space 37}88  {c |}{col 42}{res}{space 2} .2594076{col 54}{space 2} .1340334{col 65}{space 1}    1.94{col 74}{space 3}0.056{col 82}{space 4}-.0063856{col 95}{space 3} .5252008
{txt}{space 37}89  {c |}{col 42}{res}{space 2} .3044536{col 54}{space 2} .1451811{col 65}{space 1}    2.10{col 74}{space 3}0.038{col 82}{space 4} .0165541{col 95}{space 3} .5923532
{txt}{space 37}90  {c |}{col 42}{res}{space 2} .0815209{col 54}{space 2} .1082127{col 65}{space 1}    0.75{col 74}{space 3}0.453{col 82}{space 4}-.1330689{col 95}{space 3} .2961106
{txt}{space 37}91  {c |}{col 42}{res}{space 2} .1986453{col 54}{space 2} .1090218{col 65}{space 1}    1.82{col 74}{space 3}0.071{col 82}{space 4}-.0175491{col 95}{space 3} .4148397
{txt}{space 37}92  {c |}{col 42}{res}{space 2} .0813635{col 54}{space 2} .0443954{col 65}{space 1}    1.83{col 74}{space 3}0.070{col 82}{space 4}-.0066742{col 95}{space 3} .1694013
{txt}{space 37}93  {c |}{col 42}{res}{space 2} .4343401{col 54}{space 2} .1455019{col 65}{space 1}    2.99{col 74}{space 3}0.004{col 82}{space 4} .1458043{col 95}{space 3} .7228759
{txt}{space 37}94  {c |}{col 42}{res}{space 2}   .46802{col 54}{space 2} .1652287{col 65}{space 1}    2.83{col 74}{space 3}0.006{col 82}{space 4} .1403654{col 95}{space 3} .7956747
{txt}{space 37}95  {c |}{col 42}{res}{space 2} .2234752{col 54}{space 2} .1435077{col 65}{space 1}    1.56{col 74}{space 3}0.122{col 82}{space 4}-.0611059{col 95}{space 3} .5080564
{txt}{space 37}96  {c |}{col 42}{res}{space 2}  .346868{col 54}{space 2} .1532375{col 65}{space 1}    2.26{col 74}{space 3}0.026{col 82}{space 4} .0429924{col 95}{space 3} .6507437
{txt}{space 37}97  {c |}{col 42}{res}{space 2} .4029341{col 54}{space 2} .1474731{col 65}{space 1}    2.73{col 74}{space 3}0.007{col 82}{space 4} .1104893{col 95}{space 3} .6953789
{txt}{space 37}98  {c |}{col 42}{res}{space 2} .5658225{col 54}{space 2} .1827475{col 65}{space 1}    3.10{col 74}{space 3}0.003{col 82}{space 4} .2034273{col 95}{space 3} .9282177
{txt}{space 37}99  {c |}{col 42}{res}{space 2} .0926829{col 54}{space 2} .0914447{col 65}{space 1}    1.01{col 74}{space 3}0.313{col 82}{space 4}-.0886554{col 95}{space 3} .2740212
{txt}{space 36}100  {c |}{col 42}{res}{space 2} .2578783{col 54}{space 2} .1471574{col 65}{space 1}    1.75{col 74}{space 3}0.083{col 82}{space 4}-.0339404{col 95}{space 3} .5496969
{txt}{space 36}101  {c |}{col 42}{res}{space 2} .4103117{col 54}{space 2} .1330751{col 65}{space 1}    3.08{col 74}{space 3}0.003{col 82}{space 4} .1464188{col 95}{space 3} .6742046
{txt}{space 36}102  {c |}{col 42}{res}{space 2} .2563075{col 54}{space 2} .1529391{col 65}{space 1}    1.68{col 74}{space 3}0.097{col 82}{space 4}-.0469764{col 95}{space 3} .5595914
{txt}{space 36}103  {c |}{col 42}{res}{space 2} .0773919{col 54}{space 2} .1042669{col 65}{space 1}    0.74{col 74}{space 3}0.460{col 82}{space 4}-.1293733{col 95}{space 3}  .284157
{txt}{space 36}104  {c |}{col 42}{res}{space 2}-.0988512{col 54}{space 2} .0751222{col 65}{space 1}   -1.32{col 74}{space 3}0.191{col 82}{space 4}-.2478213{col 95}{space 3}  .050119
{txt}{space 36}105  {c |}{col 42}{res}{space 2} .3404037{col 54}{space 2} .1515058{col 65}{space 1}    2.25{col 74}{space 3}0.027{col 82}{space 4}  .039962{col 95}{space 3} .6408454
{txt}{space 40} {c |}
{space 36}year {c |}
{space 35}2011  {c |}{col 42}{res}{space 2}-.0041206{col 54}{space 2} .0032386{col 65}{space 1}   -1.27{col 74}{space 3}0.206{col 82}{space 4}-.0105429{col 95}{space 3} .0023016
{txt}{space 35}2012  {c |}{col 42}{res}{space 2}-.0001734{col 54}{space 2} .0045579{col 65}{space 1}   -0.04{col 74}{space 3}0.970{col 82}{space 4}-.0092119{col 95}{space 3} .0088652
{txt}{space 35}2013  {c |}{col 42}{res}{space 2}-.0013135{col 54}{space 2}   .00508{col 65}{space 1}   -0.26{col 74}{space 3}0.796{col 82}{space 4}-.0113872{col 95}{space 3} .0087603
{txt}{space 35}2014  {c |}{col 42}{res}{space 2}-.0073317{col 54}{space 2} .0071492{col 65}{space 1}   -1.03{col 74}{space 3}0.307{col 82}{space 4}-.0215089{col 95}{space 3} .0068455
{txt}{space 35}2015  {c |}{col 42}{res}{space 2}-.0148615{col 54}{space 2} .0086472{col 65}{space 1}   -1.72{col 74}{space 3}0.089{col 82}{space 4}-.0320093{col 95}{space 3} .0022862
{txt}{space 35}2016  {c |}{col 42}{res}{space 2}-.0181324{col 54}{space 2}  .007457{col 65}{space 1}   -2.43{col 74}{space 3}0.017{col 82}{space 4}  -.03292{col 95}{space 3}-.0033449
{txt}{space 35}2017  {c |}{col 42}{res}{space 2}-.0038549{col 54}{space 2} .0095819{col 65}{space 1}   -0.40{col 74}{space 3}0.688{col 82}{space 4}-.0228562{col 95}{space 3} .0151463
{txt}{space 35}2018  {c |}{col 42}{res}{space 2}-.0330039{col 54}{space 2} .0074111{col 65}{space 1}   -4.45{col 74}{space 3}0.000{col 82}{space 4}-.0477004{col 95}{space 3}-.0183073
{txt}{space 35}2019  {c |}{col 42}{res}{space 2} -.071314{col 54}{space 2} .0084741{col 65}{space 1}   -8.42{col 74}{space 3}0.000{col 82}{space 4}-.0881184{col 95}{space 3}-.0545095
{txt}{space 40} {c |}
{space 35}_cons {c |}{col 42}{res}{space 2}-.1450634{col 54}{space 2} .4124407{col 65}{space 1}   -0.35{col 74}{space 3}0.726{col 82}{space 4}-.9629488{col 95}{space 3}  .672822
{txt}{hline 41}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891278{col 50}    21{col 58}  3782598{col 69}  3782866
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1368125{col 26}{space 2} .0448884{col 37}{space 1}    3.05{col 46}{space 3}0.003{col 54}{space 4} .0477971{col 67}{space 3}  .225828
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0075368{col 26}{space 2} .0262953{col 37}{space 1}    0.29{col 46}{space 3}0.775{col 54}{space 4}-.0446076{col 67}{space 3} .0596813
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .194218{col 26}{space 2} .0482772{col 37}{space 1}    4.02{col 46}{space 3}0.000{col 54}{space 4} .0984824{col 67}{space 3} .2899535
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub +  1.gender#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub + 1.gender#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0015924{col 26}{space 2} .0186988{col 37}{space 1}    0.09{col 46}{space 3}0.932{col 54}{space 4}-.0354881{col 67}{space 3} .0386728
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
. *** MODEL 6: CONDITIONAL RESPONSES BY RACE/ETHNICITIY & POSITION -- RACIAL/ETHNIC WITHIN-'OUT-GROUP' STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0403
                                                {txt}Root MSE          =    {res} .51454

{txt}{ralign 110:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 45}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 46}{c |}{col 58}    Robust
{col 1}                         lndiversity2zeroadj{col 46}{c |} Coefficient{col 58}  std. err.{col 70}      t{col 78}   P>|t|{col 86}     [95% con{col 99}f. interval]
{hline 45}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}ln_ratio_mnmsup_mnmsub {c |}{col 46}{res}{space 2} .0495556{col 58}{space 2} .0340164{col 69}{space 1}    1.46{col 78}{space 3}0.148{col 86}{space 4}-.0179002{col 99}{space 3} .1170115
{txt}{space 34}1.minority {c |}{col 46}{res}{space 2}-.0815283{col 58}{space 2} .0069861{col 69}{space 1}  -11.67{col 78}{space 3}0.000{col 86}{space 4} -.095382{col 99}{space 3}-.0676747
{txt}{space 44} {c |}
{space 11}minority#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0423581{col 58}{space 2} .0188441{col 69}{space 1}    2.25{col 78}{space 3}0.027{col 86}{space 4} .0049895{col 99}{space 3} .0797266
{txt}{space 44} {c |}
{space 32}1.supervisor {c |}{col 46}{res}{space 2} .1285842{col 58}{space 2} .0136421{col 69}{space 1}    9.43{col 78}{space 3}0.000{col 86}{space 4} .1015315{col 99}{space 3} .1556369
{txt}{space 44} {c |}
{space 9}supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0104737{col 58}{space 2}  .027054{col 69}{space 1}    0.39{col 78}{space 3}0.699{col 86}{space 4}-.0431755{col 99}{space 3} .0641228
{txt}{space 44} {c |}
{space 25}minority#supervisor {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0162337{col 58}{space 2} .0085405{col 69}{space 1}    1.90{col 78}{space 3}0.060{col 86}{space 4}-.0007025{col 99}{space 3} .0331699
{txt}{space 44} {c |}
minority#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0272123{col 58}{space 2} .0174183{col 69}{space 1}    1.56{col 78}{space 3}0.121{col 86}{space 4} -.007329{col 99}{space 3} .0617535
{txt}{space 44} {c |}
{space 19}ln_ratio_min_tot_nmin_tot {c |}{col 46}{res}{space 2} .0540189{col 58}{space 2} .0451597{col 69}{space 1}    1.20{col 78}{space 3}0.234{col 86}{space 4}-.0355344{col 99}{space 3} .1435723
{txt}{space 38}gender {c |}{col 46}{res}{space 2}-.0395559{col 58}{space 2} .0041494{col 69}{space 1}   -9.53{col 78}{space 3}0.000{col 86}{space 4}-.0477844{col 99}{space 3}-.0313275
{txt}{space 28}topoffminority_2 {c |}{col 46}{res}{space 2} .0075102{col 58}{space 2} .0059145{col 69}{space 1}    1.27{col 78}{space 3}0.207{col 86}{space 4}-.0042184{col 99}{space 3} .0192389
{txt}{space 24}lntotworkforce_count {c |}{col 46}{res}{space 2}  .065132{col 58}{space 2}  .040231{col 69}{space 1}    1.62{col 78}{space 3}0.108{col 86}{space 4}-.0146477{col 99}{space 3} .1449116
{txt}{space 16}ln_professionals_total_ratio {c |}{col 46}{res}{space 2} .0220837{col 58}{space 2} .0502059{col 69}{space 1}    0.44{col 78}{space 3}0.661{col 86}{space 4}-.0774765{col 99}{space 3} .1216439
{txt}{space 44} {c |}
{space 36}agencyid {c |}
{space 42}2  {c |}{col 46}{res}{space 2} .2124795{col 58}{space 2} .1223652{col 69}{space 1}    1.74{col 78}{space 3}0.085{col 86}{space 4}-.0301752{col 99}{space 3} .4551342
{txt}{space 42}3  {c |}{col 46}{res}{space 2} .0329768{col 58}{space 2} .0541595{col 69}{space 1}    0.61{col 78}{space 3}0.544{col 86}{space 4}-.0744236{col 99}{space 3} .1403772
{txt}{space 42}4  {c |}{col 46}{res}{space 2} .2842209{col 58}{space 2} .1639735{col 69}{space 1}    1.73{col 78}{space 3}0.086{col 86}{space 4}-.0409447{col 99}{space 3} .6093864
{txt}{space 42}5  {c |}{col 46}{res}{space 2} .1684516{col 58}{space 2} .1273191{col 69}{space 1}    1.32{col 78}{space 3}0.189{col 86}{space 4}-.0840269{col 99}{space 3} .4209301
{txt}{space 42}6  {c |}{col 46}{res}{space 2}   .17266{col 58}{space 2} .1183506{col 69}{space 1}    1.46{col 78}{space 3}0.148{col 86}{space 4}-.0620336{col 99}{space 3} .4073536
{txt}{space 42}7  {c |}{col 46}{res}{space 2} .2443065{col 58}{space 2} .2173082{col 69}{space 1}    1.12{col 78}{space 3}0.263{col 86}{space 4}-.1866238{col 99}{space 3} .6752369
{txt}{space 42}8  {c |}{col 46}{res}{space 2} .2347865{col 58}{space 2} .1622224{col 69}{space 1}    1.45{col 78}{space 3}0.151{col 86}{space 4}-.0869065{col 99}{space 3} .5564796
{txt}{space 42}9  {c |}{col 46}{res}{space 2}-.0557392{col 58}{space 2} .0229984{col 69}{space 1}   -2.42{col 78}{space 3}0.017{col 86}{space 4}-.1013459{col 99}{space 3}-.0101324
{txt}{space 41}10  {c |}{col 46}{res}{space 2} .1923512{col 58}{space 2} .2312659{col 69}{space 1}    0.83{col 78}{space 3}0.407{col 86}{space 4}-.2662577{col 99}{space 3}   .65096
{txt}{space 41}11  {c |}{col 46}{res}{space 2} .1605167{col 58}{space 2} .1050019{col 69}{space 1}    1.53{col 78}{space 3}0.129{col 86}{space 4}-.0477061{col 99}{space 3} .3687394
{txt}{space 41}12  {c |}{col 46}{res}{space 2} .3178448{col 58}{space 2} .2145444{col 69}{space 1}    1.48{col 78}{space 3}0.142{col 86}{space 4}-.1076048{col 99}{space 3} .7432944
{txt}{space 41}13  {c |}{col 46}{res}{space 2} .3139227{col 58}{space 2}  .162476{col 69}{space 1}    1.93{col 78}{space 3}0.056{col 86}{space 4}-.0082732{col 99}{space 3} .6361186
{txt}{space 41}14  {c |}{col 46}{res}{space 2} .1573387{col 58}{space 2} .1098955{col 69}{space 1}    1.43{col 78}{space 3}0.155{col 86}{space 4}-.0605882{col 99}{space 3} .3752657
{txt}{space 41}15  {c |}{col 46}{res}{space 2} .2338113{col 58}{space 2}   .15429{col 69}{space 1}    1.52{col 78}{space 3}0.133{col 86}{space 4}-.0721515{col 99}{space 3} .5397742
{txt}{space 41}16  {c |}{col 46}{res}{space 2} .2017067{col 58}{space 2} .2880613{col 69}{space 1}    0.70{col 78}{space 3}0.485{col 86}{space 4}-.3695297{col 99}{space 3} .7729432
{txt}{space 41}17  {c |}{col 46}{res}{space 2} .0461425{col 58}{space 2} .1879433{col 69}{space 1}    0.25{col 78}{space 3}0.807{col 86}{space 4}-.3265561{col 99}{space 3} .4188412
{txt}{space 41}18  {c |}{col 46}{res}{space 2} .3088201{col 58}{space 2} .1691126{col 69}{space 1}    1.83{col 78}{space 3}0.071{col 86}{space 4}-.0265366{col 99}{space 3} .6441768
{txt}{space 41}19  {c |}{col 46}{res}{space 2} .1796704{col 58}{space 2} .1143897{col 69}{space 1}    1.57{col 78}{space 3}0.119{col 86}{space 4}-.0471687{col 99}{space 3} .4065095
{txt}{space 41}20  {c |}{col 46}{res}{space 2} .0598096{col 58}{space 2} .1202355{col 69}{space 1}    0.50{col 78}{space 3}0.620{col 86}{space 4}-.1786219{col 99}{space 3} .2982411
{txt}{space 41}21  {c |}{col 46}{res}{space 2} .2125015{col 58}{space 2} .1096043{col 69}{space 1}    1.94{col 78}{space 3}0.055{col 86}{space 4}-.0048479{col 99}{space 3}  .429851
{txt}{space 41}22  {c |}{col 46}{res}{space 2} .1480507{col 58}{space 2} .1737317{col 69}{space 1}    0.85{col 78}{space 3}0.396{col 86}{space 4}-.1964658{col 99}{space 3} .4925672
{txt}{space 41}23  {c |}{col 46}{res}{space 2}-.1039865{col 58}{space 2} .0878009{col 69}{space 1}   -1.18{col 78}{space 3}0.239{col 86}{space 4} -.278099{col 99}{space 3}  .070126
{txt}{space 41}24  {c |}{col 46}{res}{space 2}  .248194{col 58}{space 2} .1222606{col 69}{space 1}    2.03{col 78}{space 3}0.045{col 86}{space 4} .0057467{col 99}{space 3} .4906414
{txt}{space 41}25  {c |}{col 46}{res}{space 2}  .189978{col 58}{space 2}  .148744{col 69}{space 1}    1.28{col 78}{space 3}0.204{col 86}{space 4}-.1049871{col 99}{space 3}  .484943
{txt}{space 41}26  {c |}{col 46}{res}{space 2} .0525642{col 58}{space 2}  .131555{col 69}{space 1}    0.40{col 78}{space 3}0.690{col 86}{space 4}-.2083144{col 99}{space 3} .3134427
{txt}{space 41}27  {c |}{col 46}{res}{space 2} .3583969{col 58}{space 2} .1970289{col 69}{space 1}    1.82{col 78}{space 3}0.072{col 86}{space 4}-.0323188{col 99}{space 3} .7491127
{txt}{space 41}28  {c |}{col 46}{res}{space 2}-.0492249{col 58}{space 2} .1115801{col 69}{space 1}   -0.44{col 78}{space 3}0.660{col 86}{space 4}-.2704924{col 99}{space 3} .1720427
{txt}{space 41}29  {c |}{col 46}{res}{space 2} .0812223{col 58}{space 2} .1875627{col 69}{space 1}    0.43{col 78}{space 3}0.666{col 86}{space 4}-.2907216{col 99}{space 3} .4531663
{txt}{space 41}30  {c |}{col 46}{res}{space 2} .1609875{col 58}{space 2} .1734773{col 69}{space 1}    0.93{col 78}{space 3}0.356{col 86}{space 4}-.1830244{col 99}{space 3} .5049995
{txt}{space 41}31  {c |}{col 46}{res}{space 2}-.0189298{col 58}{space 2} .1791816{col 69}{space 1}   -0.11{col 78}{space 3}0.916{col 86}{space 4}-.3742537{col 99}{space 3} .3363941
{txt}{space 41}32  {c |}{col 46}{res}{space 2} .2067071{col 58}{space 2} .1423219{col 69}{space 1}    1.45{col 78}{space 3}0.149{col 86}{space 4}-.0755225{col 99}{space 3} .4889367
{txt}{space 41}33  {c |}{col 46}{res}{space 2} .1200665{col 58}{space 2} .0895714{col 69}{space 1}    1.34{col 78}{space 3}0.183{col 86}{space 4} -.057557{col 99}{space 3}   .29769
{txt}{space 41}34  {c |}{col 46}{res}{space 2}-.1495231{col 58}{space 2} .2276816{col 69}{space 1}   -0.66{col 78}{space 3}0.513{col 86}{space 4}-.6010242{col 99}{space 3}  .301978
{txt}{space 41}35  {c |}{col 46}{res}{space 2} .1409914{col 58}{space 2} .1023059{col 69}{space 1}    1.38{col 78}{space 3}0.171{col 86}{space 4} -.061885{col 99}{space 3} .3438677
{txt}{space 41}36  {c |}{col 46}{res}{space 2} .2135001{col 58}{space 2} .1349915{col 69}{space 1}    1.58{col 78}{space 3}0.117{col 86}{space 4} -.054193{col 99}{space 3} .4811933
{txt}{space 41}37  {c |}{col 46}{res}{space 2} .1978959{col 58}{space 2}  .114854{col 69}{space 1}    1.72{col 78}{space 3}0.088{col 86}{space 4} -.029864{col 99}{space 3} .4256558
{txt}{space 41}38  {c |}{col 46}{res}{space 2} .3104118{col 58}{space 2} .1960887{col 69}{space 1}    1.58{col 78}{space 3}0.116{col 86}{space 4}-.0784394{col 99}{space 3}  .699263
{txt}{space 41}39  {c |}{col 46}{res}{space 2} .2166658{col 58}{space 2} .1176582{col 69}{space 1}    1.84{col 78}{space 3}0.068{col 86}{space 4}-.0166547{col 99}{space 3} .4499863
{txt}{space 41}40  {c |}{col 46}{res}{space 2} .0440536{col 58}{space 2} .0782197{col 69}{space 1}    0.56{col 78}{space 3}0.575{col 86}{space 4} -.111059{col 99}{space 3} .1991661
{txt}{space 41}41  {c |}{col 46}{res}{space 2} .1833701{col 58}{space 2} .1718141{col 69}{space 1}    1.07{col 78}{space 3}0.288{col 86}{space 4}-.1573436{col 99}{space 3} .5240838
{txt}{space 41}42  {c |}{col 46}{res}{space 2} .2203576{col 58}{space 2} .1607037{col 69}{space 1}    1.37{col 78}{space 3}0.173{col 86}{space 4} -.098324{col 99}{space 3} .5390391
{txt}{space 41}43  {c |}{col 46}{res}{space 2} .0064976{col 58}{space 2} .0739613{col 69}{space 1}    0.09{col 78}{space 3}0.930{col 86}{space 4}-.1401705{col 99}{space 3} .1531658
{txt}{space 41}44  {c |}{col 46}{res}{space 2} .2586034{col 58}{space 2} .1372581{col 69}{space 1}    1.88{col 78}{space 3}0.062{col 86}{space 4}-.0135847{col 99}{space 3} .5307914
{txt}{space 41}45  {c |}{col 46}{res}{space 2} .2211519{col 58}{space 2} .1203595{col 69}{space 1}    1.84{col 78}{space 3}0.069{col 86}{space 4}-.0175256{col 99}{space 3} .4598293
{txt}{space 41}46  {c |}{col 46}{res}{space 2} .1273702{col 58}{space 2} .2126247{col 69}{space 1}    0.60{col 78}{space 3}0.550{col 86}{space 4}-.2942725{col 99}{space 3}  .549013
{txt}{space 41}47  {c |}{col 46}{res}{space 2} .1544597{col 58}{space 2} .0924305{col 69}{space 1}    1.67{col 78}{space 3}0.098{col 86}{space 4}-.0288335{col 99}{space 3}  .337753
{txt}{space 41}48  {c |}{col 46}{res}{space 2} .2400215{col 58}{space 2} .1889069{col 69}{space 1}    1.27{col 78}{space 3}0.207{col 86}{space 4} -.134588{col 99}{space 3}  .614631
{txt}{space 41}49  {c |}{col 46}{res}{space 2}  .332737{col 58}{space 2} .2043829{col 69}{space 1}    1.63{col 78}{space 3}0.107{col 86}{space 4} -.072562{col 99}{space 3}  .738036
{txt}{space 41}50  {c |}{col 46}{res}{space 2} .3455754{col 58}{space 2} .1845318{col 69}{space 1}    1.87{col 78}{space 3}0.064{col 86}{space 4} -.020358{col 99}{space 3} .7115088
{txt}{space 41}51  {c |}{col 46}{res}{space 2} .3387362{col 58}{space 2} .2318839{col 69}{space 1}    1.46{col 78}{space 3}0.147{col 86}{space 4}-.1210983{col 99}{space 3} .7985708
{txt}{space 41}52  {c |}{col 46}{res}{space 2} .2361361{col 58}{space 2} .2314511{col 69}{space 1}    1.02{col 78}{space 3}0.310{col 86}{space 4}-.2228401{col 99}{space 3} .6951123
{txt}{space 41}53  {c |}{col 46}{res}{space 2} .2722725{col 58}{space 2} .1662882{col 69}{space 1}    1.64{col 78}{space 3}0.105{col 86}{space 4}-.0574833{col 99}{space 3} .6020283
{txt}{space 41}54  {c |}{col 46}{res}{space 2} .2919686{col 58}{space 2} .1841924{col 69}{space 1}    1.59{col 78}{space 3}0.116{col 86}{space 4}-.0732919{col 99}{space 3} .6572291
{txt}{space 41}55  {c |}{col 46}{res}{space 2} .4166893{col 58}{space 2}  .235368{col 69}{space 1}    1.77{col 78}{space 3}0.080{col 86}{space 4}-.0500543{col 99}{space 3}  .883433
{txt}{space 41}56  {c |}{col 46}{res}{space 2} .2486483{col 58}{space 2} .2412732{col 69}{space 1}    1.03{col 78}{space 3}0.305{col 86}{space 4}-.2298055{col 99}{space 3} .7271022
{txt}{space 41}57  {c |}{col 46}{res}{space 2} .3177738{col 58}{space 2} .3041578{col 69}{space 1}    1.04{col 78}{space 3}0.299{col 86}{space 4}-.2853825{col 99}{space 3} .9209302
{txt}{space 41}58  {c |}{col 46}{res}{space 2} .1979476{col 58}{space 2} .1744636{col 69}{space 1}    1.13{col 78}{space 3}0.259{col 86}{space 4}-.1480202{col 99}{space 3} .5439155
{txt}{space 41}59  {c |}{col 46}{res}{space 2} .1963024{col 58}{space 2} .2093655{col 69}{space 1}    0.94{col 78}{space 3}0.351{col 86}{space 4}-.2188773{col 99}{space 3} .6114821
{txt}{space 41}60  {c |}{col 46}{res}{space 2} .1449048{col 58}{space 2} .1035029{col 69}{space 1}    1.40{col 78}{space 3}0.164{col 86}{space 4}-.0603453{col 99}{space 3} .3501548
{txt}{space 41}61  {c |}{col 46}{res}{space 2} .1363538{col 58}{space 2}   .11047{col 69}{space 1}    1.23{col 78}{space 3}0.220{col 86}{space 4}-.0827124{col 99}{space 3} .3554199
{txt}{space 41}62  {c |}{col 46}{res}{space 2} .3196379{col 58}{space 2} .2067009{col 69}{space 1}    1.55{col 78}{space 3}0.125{col 86}{space 4}-.0902577{col 99}{space 3} .7295335
{txt}{space 41}63  {c |}{col 46}{res}{space 2} .3902752{col 58}{space 2} .2011325{col 69}{space 1}    1.94{col 78}{space 3}0.055{col 86}{space 4}-.0085781{col 99}{space 3} .7891285
{txt}{space 41}64  {c |}{col 46}{res}{space 2} .4011471{col 58}{space 2} .2109485{col 69}{space 1}    1.90{col 78}{space 3}0.060{col 86}{space 4}-.0171718{col 99}{space 3} .8194659
{txt}{space 41}65  {c |}{col 46}{res}{space 2} .2127455{col 58}{space 2} .1213613{col 69}{space 1}    1.75{col 78}{space 3}0.083{col 86}{space 4}-.0279185{col 99}{space 3} .4534096
{txt}{space 41}66  {c |}{col 46}{res}{space 2} .1913694{col 58}{space 2} .2237713{col 69}{space 1}    0.86{col 78}{space 3}0.394{col 86}{space 4}-.2523775{col 99}{space 3} .6351163
{txt}{space 41}67  {c |}{col 46}{res}{space 2} .2227186{col 58}{space 2} .1368401{col 69}{space 1}    1.63{col 78}{space 3}0.107{col 86}{space 4}-.0486405{col 99}{space 3} .4940777
{txt}{space 41}68  {c |}{col 46}{res}{space 2} .2804202{col 58}{space 2} .1526894{col 69}{space 1}    1.84{col 78}{space 3}0.069{col 86}{space 4}-.0223686{col 99}{space 3} .5832091
{txt}{space 41}69  {c |}{col 46}{res}{space 2} .1415749{col 58}{space 2}   .12273{col 69}{space 1}    1.15{col 78}{space 3}0.251{col 86}{space 4}-.1018034{col 99}{space 3} .3849532
{txt}{space 41}70  {c |}{col 46}{res}{space 2} .3491404{col 58}{space 2} .2109404{col 69}{space 1}    1.66{col 78}{space 3}0.101{col 86}{space 4}-.0691624{col 99}{space 3} .7674432
{txt}{space 41}71  {c |}{col 46}{res}{space 2}-.1083088{col 58}{space 2} .1821142{col 69}{space 1}   -0.59{col 78}{space 3}0.553{col 86}{space 4}-.4694481{col 99}{space 3} .2528306
{txt}{space 41}72  {c |}{col 46}{res}{space 2} .2008883{col 58}{space 2} .1184368{col 69}{space 1}    1.70{col 78}{space 3}0.093{col 86}{space 4}-.0339764{col 99}{space 3}  .435753
{txt}{space 41}73  {c |}{col 46}{res}{space 2} .4255182{col 58}{space 2} .1921848{col 69}{space 1}    2.21{col 78}{space 3}0.029{col 86}{space 4} .0444086{col 99}{space 3} .8066279
{txt}{space 41}74  {c |}{col 46}{res}{space 2} .1519453{col 58}{space 2} .1023511{col 69}{space 1}    1.48{col 78}{space 3}0.141{col 86}{space 4}-.0510208{col 99}{space 3} .3549113
{txt}{space 41}75  {c |}{col 46}{res}{space 2} .0691141{col 58}{space 2}  .150595{col 69}{space 1}    0.46{col 78}{space 3}0.647{col 86}{space 4}-.2295215{col 99}{space 3} .3677497
{txt}{space 41}76  {c |}{col 46}{res}{space 2} .2950556{col 58}{space 2} .1725564{col 69}{space 1}    1.71{col 78}{space 3}0.090{col 86}{space 4}-.0471302{col 99}{space 3} .6372414
{txt}{space 41}77  {c |}{col 46}{res}{space 2} .2221297{col 58}{space 2} .1712962{col 69}{space 1}    1.30{col 78}{space 3}0.198{col 86}{space 4}-.1175571{col 99}{space 3} .5618165
{txt}{space 41}78  {c |}{col 46}{res}{space 2} .2693742{col 58}{space 2} .1092546{col 69}{space 1}    2.47{col 78}{space 3}0.015{col 86}{space 4} .0527182{col 99}{space 3} .4860303
{txt}{space 41}79  {c |}{col 46}{res}{space 2}-.0169269{col 58}{space 2} .0254438{col 69}{space 1}   -0.67{col 78}{space 3}0.507{col 86}{space 4}-.0673829{col 99}{space 3}  .033529
{txt}{space 41}80  {c |}{col 46}{res}{space 2} .4347694{col 58}{space 2} .2178208{col 69}{space 1}    2.00{col 78}{space 3}0.049{col 86}{space 4} .0028226{col 99}{space 3} .8667161
{txt}{space 41}81  {c |}{col 46}{res}{space 2} .1644273{col 58}{space 2} .2384562{col 69}{space 1}    0.69{col 78}{space 3}0.492{col 86}{space 4}-.3084403{col 99}{space 3}  .637295
{txt}{space 41}82  {c |}{col 46}{res}{space 2} .2352804{col 58}{space 2} .2041287{col 69}{space 1}    1.15{col 78}{space 3}0.252{col 86}{space 4}-.1695144{col 99}{space 3} .6400753
{txt}{space 41}83  {c |}{col 46}{res}{space 2} .3446905{col 58}{space 2} .1689881{col 69}{space 1}    2.04{col 78}{space 3}0.044{col 86}{space 4} .0095808{col 99}{space 3} .6798002
{txt}{space 41}84  {c |}{col 46}{res}{space 2} .2860837{col 58}{space 2} .2073057{col 69}{space 1}    1.38{col 78}{space 3}0.171{col 86}{space 4}-.1250112{col 99}{space 3} .6971786
{txt}{space 41}85  {c |}{col 46}{res}{space 2} .3059713{col 58}{space 2} .1612283{col 69}{space 1}    1.90{col 78}{space 3}0.061{col 86}{space 4}-.0137505{col 99}{space 3} .6256931
{txt}{space 41}86  {c |}{col 46}{res}{space 2} .3268196{col 58}{space 2} .2403497{col 69}{space 1}    1.36{col 78}{space 3}0.177{col 86}{space 4}-.1498028{col 99}{space 3}  .803442
{txt}{space 41}87  {c |}{col 46}{res}{space 2} .3814955{col 58}{space 2} .2404095{col 69}{space 1}    1.59{col 78}{space 3}0.116{col 86}{space 4}-.0952455{col 99}{space 3} .8582365
{txt}{space 41}88  {c |}{col 46}{res}{space 2}  .170345{col 58}{space 2}  .169084{col 69}{space 1}    1.01{col 78}{space 3}0.316{col 86}{space 4}-.1649549{col 99}{space 3} .5056449
{txt}{space 41}89  {c |}{col 46}{res}{space 2} .2293782{col 58}{space 2} .1642186{col 69}{space 1}    1.40{col 78}{space 3}0.165{col 86}{space 4}-.0962734{col 99}{space 3} .5550298
{txt}{space 41}90  {c |}{col 46}{res}{space 2} .0210927{col 58}{space 2} .0839962{col 69}{space 1}    0.25{col 78}{space 3}0.802{col 86}{space 4}-.1454749{col 99}{space 3} .1876604
{txt}{space 41}91  {c |}{col 46}{res}{space 2} .1426714{col 58}{space 2} .1180859{col 69}{space 1}    1.21{col 78}{space 3}0.230{col 86}{space 4}-.0914973{col 99}{space 3} .3768401
{txt}{space 41}92  {c |}{col 46}{res}{space 2} .0817086{col 58}{space 2} .0597169{col 69}{space 1}    1.37{col 78}{space 3}0.174{col 86}{space 4}-.0367123{col 99}{space 3} .2001295
{txt}{space 41}93  {c |}{col 46}{res}{space 2} .3548622{col 58}{space 2} .1729526{col 69}{space 1}    2.05{col 78}{space 3}0.043{col 86}{space 4} .0118906{col 99}{space 3} .6978337
{txt}{space 41}94  {c |}{col 46}{res}{space 2} .4498895{col 58}{space 2} .2123047{col 69}{space 1}    2.12{col 78}{space 3}0.036{col 86}{space 4} .0288812{col 99}{space 3} .8708978
{txt}{space 41}95  {c |}{col 46}{res}{space 2} .1704001{col 58}{space 2} .2083412{col 69}{space 1}    0.82{col 78}{space 3}0.415{col 86}{space 4}-.2427482{col 99}{space 3} .5835485
{txt}{space 41}96  {c |}{col 46}{res}{space 2} .2957576{col 58}{space 2} .1882792{col 69}{space 1}    1.57{col 78}{space 3}0.119{col 86}{space 4}-.0776071{col 99}{space 3} .6691223
{txt}{space 41}97  {c |}{col 46}{res}{space 2} .3335875{col 58}{space 2} .1538589{col 69}{space 1}    2.17{col 78}{space 3}0.032{col 86}{space 4} .0284795{col 99}{space 3} .6386954
{txt}{space 41}98  {c |}{col 46}{res}{space 2} .4430025{col 58}{space 2} .2215888{col 69}{space 1}    2.00{col 78}{space 3}0.048{col 86}{space 4} .0035835{col 99}{space 3} .8824214
{txt}{space 41}99  {c |}{col 46}{res}{space 2} .0445754{col 58}{space 2} .0561419{col 69}{space 1}    0.79{col 78}{space 3}0.429{col 86}{space 4}-.0667561{col 99}{space 3}  .155907
{txt}{space 40}100  {c |}{col 46}{res}{space 2} .2104897{col 58}{space 2} .2104314{col 69}{space 1}    1.00{col 78}{space 3}0.319{col 86}{space 4}-.2068037{col 99}{space 3}  .627783
{txt}{space 40}101  {c |}{col 46}{res}{space 2} .3687378{col 58}{space 2} .1667254{col 69}{space 1}    2.21{col 78}{space 3}0.029{col 86}{space 4}  .038115{col 99}{space 3} .6993605
{txt}{space 40}102  {c |}{col 46}{res}{space 2} .2788332{col 58}{space 2} .2137971{col 69}{space 1}    1.30{col 78}{space 3}0.195{col 86}{space 4}-.1451345{col 99}{space 3} .7028008
{txt}{space 40}103  {c |}{col 46}{res}{space 2} .0811997{col 58}{space 2} .1173223{col 69}{space 1}    0.69{col 78}{space 3}0.490{col 86}{space 4}-.1514549{col 99}{space 3} .3138542
{txt}{space 40}104  {c |}{col 46}{res}{space 2}-.1591134{col 58}{space 2} .0604356{col 69}{space 1}   -2.63{col 78}{space 3}0.010{col 86}{space 4}-.2789594{col 99}{space 3}-.0392674
{txt}{space 40}105  {c |}{col 46}{res}{space 2} .2286706{col 58}{space 2} .1995644{col 69}{space 1}    1.15{col 78}{space 3}0.254{col 86}{space 4}-.1670731{col 99}{space 3} .6244143
{txt}{space 44} {c |}
{space 40}year {c |}
{space 39}2011  {c |}{col 46}{res}{space 2}-.0023485{col 58}{space 2}  .003762{col 69}{space 1}   -0.62{col 78}{space 3}0.534{col 86}{space 4}-.0098087{col 99}{space 3} .0051118
{txt}{space 39}2012  {c |}{col 46}{res}{space 2} .0046855{col 58}{space 2} .0045302{col 69}{space 1}    1.03{col 78}{space 3}0.303{col 86}{space 4}-.0042981{col 99}{space 3} .0136691
{txt}{space 39}2013  {c |}{col 46}{res}{space 2} .0027048{col 58}{space 2} .0056327{col 69}{space 1}    0.48{col 78}{space 3}0.632{col 86}{space 4} -.008465{col 99}{space 3} .0138746
{txt}{space 39}2014  {c |}{col 46}{res}{space 2}-.0023247{col 58}{space 2} .0066073{col 69}{space 1}   -0.35{col 78}{space 3}0.726{col 86}{space 4}-.0154272{col 99}{space 3} .0107778
{txt}{space 39}2015  {c |}{col 46}{res}{space 2}-.0102001{col 58}{space 2} .0080232{col 69}{space 1}   -1.27{col 78}{space 3}0.206{col 86}{space 4}-.0261104{col 99}{space 3} .0057103
{txt}{space 39}2016  {c |}{col 46}{res}{space 2}-.0131303{col 58}{space 2} .0079989{col 69}{space 1}   -1.64{col 78}{space 3}0.104{col 86}{space 4}-.0289923{col 99}{space 3} .0027318
{txt}{space 39}2017  {c |}{col 46}{res}{space 2}-.0029164{col 58}{space 2} .0117991{col 69}{space 1}   -0.25{col 78}{space 3}0.805{col 86}{space 4}-.0263144{col 99}{space 3} .0204816
{txt}{space 39}2018  {c |}{col 46}{res}{space 2}-.0293178{col 58}{space 2}  .010778{col 69}{space 1}   -2.72{col 78}{space 3}0.008{col 86}{space 4}-.0506911{col 99}{space 3}-.0079446
{txt}{space 39}2019  {c |}{col 46}{res}{space 2}-.0685313{col 58}{space 2} .0121882{col 69}{space 1}   -5.62{col 78}{space 3}0.000{col 86}{space 4}-.0927009{col 99}{space 3}-.0443616
{txt}{space 44} {c |}
{space 39}_cons {c |}{col 46}{res}{space 2} .0423609{col 58}{space 2} .5061582{col 69}{space 1}    0.08{col 78}{space 3}0.933{col 86}{space 4}-.9613698{col 99}{space 3} 1.046092
{txt}{hline 45}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891455{col 50}    21{col 58}  3782952{col 69}  3783219
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0495556{col 26}{space 2} .0340164{col 37}{space 1}    1.46{col 46}{space 3}0.148{col 54}{space 4}-.0179002{col 67}{space 3} .1170115
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0423581{col 26}{space 2} .0188441{col 37}{space 1}    2.25{col 46}{space 3}0.027{col 54}{space 4} .0049895{col 67}{space 3} .0797266
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0600293{col 26}{space 2} .0405647{col 37}{space 1}    1.48{col 46}{space 3}0.142{col 54}{space 4}-.0204121{col 67}{space 3} .1404707
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub +  1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub + 1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0695703{col 26}{space 2} .0162755{col 37}{space 1}    4.27{col 46}{space 3}0.000{col 54}{space 4} .0372954{col 67}{space 3} .1018452
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES 
.  
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub +  1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0272123{col 26}{space 2} .0174183{col 37}{space 1}    1.56{col 46}{space 3}0.121{col 54}{space 4} -.007329{col 67}{space 3} .0617535
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
.    
. *** MODEL 7: CONDITIONAL RESPONSES BY GENDER & POSITION -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.women_het##i.supervisor    ln_ratio_fem_tot_men_tot   minority   topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(24, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0407
                                                {txt}Root MSE          =    {res} .51443

{txt}{ralign 109:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 44}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 45}{c |}{col 57}    Robust
{col 1}                        lndiversity2zeroadj{col 45}{c |} Coefficient{col 57}  std. err.{col 69}      t{col 77}   P>|t|{col 85}     [95% con{col 98}f. interval]
{hline 44}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}ln_ratio_fmsup_fmsub {c |}{col 45}{res}{space 2} .1357575{col 57}{space 2} .0450905{col 68}{space 1}    3.01{col 77}{space 3}0.003{col 85}{space 4} .0463414{col 98}{space 3} .2251736
{txt}{space 43} {c |}
{space 34}women_het {c |}
{space 41}1  {c |}{col 45}{res}{space 2}-.0270601{col 57}{space 2} .0112023{col 68}{space 1}   -2.42{col 77}{space 3}0.017{col 85}{space 4}-.0492747{col 98}{space 3}-.0048455
{txt}{space 41}2  {c |}{col 45}{res}{space 2}  -.05768{col 57}{space 2} .0105358{col 68}{space 1}   -5.47{col 77}{space 3}0.000{col 85}{space 4} -.078573{col 98}{space 3}-.0367871
{txt}{space 43} {c |}
{space 11}women_het#c.ln_ratio_fmsup_fmsub {c |}
{space 41}1  {c |}{col 45}{res}{space 2} .0011512{col 57}{space 2} .0281804{col 68}{space 1}    0.04{col 77}{space 3}0.967{col 85}{space 4}-.0547317{col 98}{space 3}  .057034
{txt}{space 41}2  {c |}{col 45}{res}{space 2} .0241578{col 57}{space 2} .0284199{col 68}{space 1}    0.85{col 77}{space 3}0.397{col 85}{space 4}-.0321998{col 98}{space 3} .0805155
{txt}{space 43} {c |}
{space 31}1.supervisor {c |}{col 45}{res}{space 2} .1459008{col 57}{space 2} .0210052{col 68}{space 1}    6.95{col 77}{space 3}0.000{col 85}{space 4} .1042467{col 98}{space 3} .1875548
{txt}{space 43} {c |}
{space 10}supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 41}1  {c |}{col 45}{res}{space 2} .0577398{col 57}{space 2} .0419213{col 68}{space 1}    1.38{col 77}{space 3}0.171{col 85}{space 4}-.0253918{col 98}{space 3} .1408713
{txt}{space 43} {c |}
{space 23}women_het#supervisor {c |}
{space 39}1 1  {c |}{col 45}{res}{space 2} .0040249{col 57}{space 2} .0134254{col 68}{space 1}    0.30{col 77}{space 3}0.765{col 85}{space 4}-.0225981{col 98}{space 3}  .030648
{txt}{space 39}2 1  {c |}{col 45}{res}{space 2} .0023059{col 57}{space 2} .0197466{col 68}{space 1}    0.12{col 77}{space 3}0.907{col 85}{space 4}-.0368524{col 98}{space 3} .0414641
{txt}{space 43} {c |}
women_het#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 39}1 1  {c |}{col 45}{res}{space 2} .0064659{col 57}{space 2}  .029295{col 68}{space 1}    0.22{col 77}{space 3}0.826{col 85}{space 4}-.0516271{col 98}{space 3} .0645589
{txt}{space 39}2 1  {c |}{col 45}{res}{space 2}-.0274444{col 57}{space 2}  .039576{col 68}{space 1}   -0.69{col 77}{space 3}0.490{col 85}{space 4} -.105925{col 98}{space 3} .0510362
{txt}{space 43} {c |}
{space 19}ln_ratio_fem_tot_men_tot {c |}{col 45}{res}{space 2}-.0066833{col 57}{space 2} .0554815{col 68}{space 1}   -0.12{col 77}{space 3}0.904{col 85}{space 4}-.1167052{col 98}{space 3} .1033387
{txt}{space 35}minority {c |}{col 45}{res}{space 2}-.0768847{col 57}{space 2} .0036523{col 68}{space 1}  -21.05{col 77}{space 3}0.000{col 85}{space 4}-.0841273{col 98}{space 3}-.0696421
{txt}{space 29}topoffgender_2 {c |}{col 45}{res}{space 2} -.002832{col 57}{space 2} .0045074{col 68}{space 1}   -0.63{col 77}{space 3}0.531{col 85}{space 4}-.0117703{col 98}{space 3} .0061064
{txt}{space 23}lntotworkforce_count {c |}{col 45}{res}{space 2} .0762127{col 57}{space 2} .0321386{col 68}{space 1}    2.37{col 77}{space 3}0.020{col 85}{space 4} .0124807{col 98}{space 3} .1399447
{txt}{space 15}ln_professionals_total_ratio {c |}{col 45}{res}{space 2} .0071171{col 57}{space 2} .0412562{col 68}{space 1}    0.17{col 77}{space 3}0.863{col 85}{space 4}-.0746955{col 98}{space 3} .0889296
{txt}{space 43} {c |}
{space 35}agencyid {c |}
{space 41}2  {c |}{col 45}{res}{space 2}   .31469{col 57}{space 2} .1134664{col 68}{space 1}    2.77{col 77}{space 3}0.007{col 85}{space 4} .0896818{col 98}{space 3} .5396982
{txt}{space 41}3  {c |}{col 45}{res}{space 2} .0937172{col 57}{space 2} .0535879{col 68}{space 1}    1.75{col 77}{space 3}0.083{col 85}{space 4}-.0125496{col 98}{space 3}  .199984
{txt}{space 41}4  {c |}{col 45}{res}{space 2} .4398165{col 57}{space 2} .1488635{col 68}{space 1}    2.95{col 77}{space 3}0.004{col 85}{space 4} .1446146{col 98}{space 3} .7350183
{txt}{space 41}5  {c |}{col 45}{res}{space 2} .2668848{col 57}{space 2} .1035749{col 68}{space 1}    2.58{col 77}{space 3}0.011{col 85}{space 4} .0614919{col 98}{space 3} .4722778
{txt}{space 41}6  {c |}{col 45}{res}{space 2} .2527278{col 57}{space 2} .1099371{col 68}{space 1}    2.30{col 77}{space 3}0.024{col 85}{space 4} .0347184{col 98}{space 3} .4707371
{txt}{space 41}7  {c |}{col 45}{res}{space 2} .3628518{col 57}{space 2} .1813465{col 68}{space 1}    2.00{col 77}{space 3}0.048{col 85}{space 4} .0032349{col 98}{space 3} .7224687
{txt}{space 41}8  {c |}{col 45}{res}{space 2} .3068236{col 57}{space 2} .1416729{col 68}{space 1}    2.17{col 77}{space 3}0.033{col 85}{space 4}  .025881{col 98}{space 3} .5877662
{txt}{space 41}9  {c |}{col 45}{res}{space 2} -.012087{col 57}{space 2} .0227868{col 68}{space 1}   -0.53{col 77}{space 3}0.597{col 85}{space 4} -.057274{col 98}{space 3} .0331001
{txt}{space 40}10  {c |}{col 45}{res}{space 2} .2538764{col 57}{space 2} .1601236{col 68}{space 1}    1.59{col 77}{space 3}0.116{col 85}{space 4}-.0636548{col 98}{space 3} .5714075
{txt}{space 40}11  {c |}{col 45}{res}{space 2} .2161423{col 57}{space 2} .1175864{col 68}{space 1}    1.84{col 77}{space 3}0.069{col 85}{space 4} -.017036{col 98}{space 3} .4493206
{txt}{space 40}12  {c |}{col 45}{res}{space 2} .3801271{col 57}{space 2} .1694402{col 68}{space 1}    2.24{col 77}{space 3}0.027{col 85}{space 4} .0441207{col 98}{space 3} .7161334
{txt}{space 40}13  {c |}{col 45}{res}{space 2} .3620703{col 57}{space 2} .1427207{col 68}{space 1}    2.54{col 77}{space 3}0.013{col 85}{space 4} .0790498{col 98}{space 3} .6450909
{txt}{space 40}14  {c |}{col 45}{res}{space 2}  .165296{col 57}{space 2} .1050291{col 68}{space 1}    1.57{col 77}{space 3}0.119{col 85}{space 4}-.0429806{col 98}{space 3} .3735726
{txt}{space 40}15  {c |}{col 45}{res}{space 2} .3052927{col 57}{space 2} .1158553{col 68}{space 1}    2.64{col 77}{space 3}0.010{col 85}{space 4} .0755472{col 98}{space 3} .5350381
{txt}{space 40}16  {c |}{col 45}{res}{space 2} .4824702{col 57}{space 2} .1958498{col 68}{space 1}    2.46{col 77}{space 3}0.015{col 85}{space 4} .0940927{col 98}{space 3} .8708476
{txt}{space 40}17  {c |}{col 45}{res}{space 2} .1333839{col 57}{space 2} .1562657{col 68}{space 1}    0.85{col 77}{space 3}0.395{col 85}{space 4}-.1764968{col 98}{space 3} .4432647
{txt}{space 40}18  {c |}{col 45}{res}{space 2}  .360112{col 57}{space 2}  .151898{col 68}{space 1}    2.37{col 77}{space 3}0.020{col 85}{space 4} .0588925{col 98}{space 3} .6613316
{txt}{space 40}19  {c |}{col 45}{res}{space 2} .2256988{col 57}{space 2} .0980394{col 68}{space 1}    2.30{col 77}{space 3}0.023{col 85}{space 4}  .031283{col 98}{space 3} .4201146
{txt}{space 40}20  {c |}{col 45}{res}{space 2} .3081507{col 57}{space 2} .1581168{col 68}{space 1}    1.95{col 77}{space 3}0.054{col 85}{space 4}-.0054008{col 98}{space 3} .6217022
{txt}{space 40}21  {c |}{col 45}{res}{space 2} .2721238{col 57}{space 2} .1185307{col 68}{space 1}    2.30{col 77}{space 3}0.024{col 85}{space 4} .0370731{col 98}{space 3} .5071746
{txt}{space 40}22  {c |}{col 45}{res}{space 2} .2745734{col 57}{space 2} .1427369{col 68}{space 1}    1.92{col 77}{space 3}0.057{col 85}{space 4}-.0084792{col 98}{space 3} .5576261
{txt}{space 40}23  {c |}{col 45}{res}{space 2}-.0863896{col 57}{space 2} .0512291{col 68}{space 1}   -1.69{col 77}{space 3}0.095{col 85}{space 4}-.1879788{col 98}{space 3} .0151997
{txt}{space 40}24  {c |}{col 45}{res}{space 2} .2969295{col 57}{space 2} .0953255{col 68}{space 1}    3.11{col 77}{space 3}0.002{col 85}{space 4} .1078955{col 98}{space 3} .4859635
{txt}{space 40}25  {c |}{col 45}{res}{space 2} .1983997{col 57}{space 2}  .134619{col 68}{space 1}    1.47{col 77}{space 3}0.144{col 85}{space 4}-.0685549{col 98}{space 3} .4653543
{txt}{space 40}26  {c |}{col 45}{res}{space 2} .1051723{col 57}{space 2} .1099568{col 68}{space 1}    0.96{col 77}{space 3}0.341{col 85}{space 4}-.1128762{col 98}{space 3} .3232208
{txt}{space 40}27  {c |}{col 45}{res}{space 2} .3926458{col 57}{space 2} .1566062{col 68}{space 1}    2.51{col 77}{space 3}0.014{col 85}{space 4} .0820899{col 98}{space 3} .7032018
{txt}{space 40}28  {c |}{col 45}{res}{space 2} .0052038{col 57}{space 2} .0722668{col 68}{space 1}    0.07{col 77}{space 3}0.943{col 85}{space 4} -.138104{col 98}{space 3} .1485117
{txt}{space 40}29  {c |}{col 45}{res}{space 2} .1119917{col 57}{space 2} .1298313{col 68}{space 1}    0.86{col 77}{space 3}0.390{col 85}{space 4}-.1454686{col 98}{space 3}  .369452
{txt}{space 40}30  {c |}{col 45}{res}{space 2} .1453426{col 57}{space 2} .1210633{col 68}{space 1}    1.20{col 77}{space 3}0.233{col 85}{space 4}-.0947305{col 98}{space 3} .3854156
{txt}{space 40}31  {c |}{col 45}{res}{space 2}-.0134964{col 57}{space 2} .1450266{col 68}{space 1}   -0.09{col 77}{space 3}0.926{col 85}{space 4}-.3010895{col 98}{space 3} .2740968
{txt}{space 40}32  {c |}{col 45}{res}{space 2} .2545004{col 57}{space 2} .1124204{col 68}{space 1}    2.26{col 77}{space 3}0.026{col 85}{space 4} .0315667{col 98}{space 3} .4774342
{txt}{space 40}33  {c |}{col 45}{res}{space 2} .1531861{col 57}{space 2} .0688335{col 68}{space 1}    2.23{col 77}{space 3}0.028{col 85}{space 4} .0166866{col 98}{space 3} .2896856
{txt}{space 40}34  {c |}{col 45}{res}{space 2} .1569069{col 57}{space 2} .1191619{col 68}{space 1}    1.32{col 77}{space 3}0.191{col 85}{space 4}-.0793957{col 98}{space 3} .3932094
{txt}{space 40}35  {c |}{col 45}{res}{space 2} .1893957{col 57}{space 2}  .093236{col 68}{space 1}    2.03{col 77}{space 3}0.045{col 85}{space 4} .0045052{col 98}{space 3} .3742862
{txt}{space 40}36  {c |}{col 45}{res}{space 2} .2474736{col 57}{space 2} .1172383{col 68}{space 1}    2.11{col 77}{space 3}0.037{col 85}{space 4} .0149857{col 98}{space 3} .4799614
{txt}{space 40}37  {c |}{col 45}{res}{space 2} .2444011{col 57}{space 2} .1109346{col 68}{space 1}    2.20{col 77}{space 3}0.030{col 85}{space 4} .0244136{col 98}{space 3} .4643885
{txt}{space 40}38  {c |}{col 45}{res}{space 2} .3951086{col 57}{space 2} .1621989{col 68}{space 1}    2.44{col 77}{space 3}0.017{col 85}{space 4} .0734621{col 98}{space 3} .7167552
{txt}{space 40}39  {c |}{col 45}{res}{space 2} .2193634{col 57}{space 2} .1149307{col 68}{space 1}    1.91{col 77}{space 3}0.059{col 85}{space 4}-.0085486{col 98}{space 3} .4472753
{txt}{space 40}40  {c |}{col 45}{res}{space 2} .0311388{col 57}{space 2} .0716356{col 68}{space 1}    0.43{col 77}{space 3}0.665{col 85}{space 4}-.1109171{col 98}{space 3} .1731948
{txt}{space 40}41  {c |}{col 45}{res}{space 2} .3097158{col 57}{space 2} .1467504{col 68}{space 1}    2.11{col 77}{space 3}0.037{col 85}{space 4} .0187042{col 98}{space 3} .6007274
{txt}{space 40}42  {c |}{col 45}{res}{space 2} .3204484{col 57}{space 2} .1207602{col 68}{space 1}    2.65{col 77}{space 3}0.009{col 85}{space 4} .0809764{col 98}{space 3} .5599204
{txt}{space 40}43  {c |}{col 45}{res}{space 2} .1077586{col 57}{space 2} .0469446{col 68}{space 1}    2.30{col 77}{space 3}0.024{col 85}{space 4} .0146658{col 98}{space 3} .2008515
{txt}{space 40}44  {c |}{col 45}{res}{space 2} .3566365{col 57}{space 2}  .101937{col 68}{space 1}    3.50{col 77}{space 3}0.001{col 85}{space 4} .1544916{col 98}{space 3} .5587815
{txt}{space 40}45  {c |}{col 45}{res}{space 2} .3057883{col 57}{space 2}  .122416{col 68}{space 1}    2.50{col 77}{space 3}0.014{col 85}{space 4} .0630328{col 98}{space 3} .5485438
{txt}{space 40}46  {c |}{col 45}{res}{space 2} .2898484{col 57}{space 2} .1865958{col 68}{space 1}    1.55{col 77}{space 3}0.123{col 85}{space 4} -.080178{col 98}{space 3} .6598749
{txt}{space 40}47  {c |}{col 45}{res}{space 2} .2057113{col 57}{space 2} .0855702{col 68}{space 1}    2.40{col 77}{space 3}0.018{col 85}{space 4} .0360224{col 98}{space 3} .3754003
{txt}{space 40}48  {c |}{col 45}{res}{space 2} .2316815{col 57}{space 2} .1327873{col 68}{space 1}    1.74{col 77}{space 3}0.084{col 85}{space 4}-.0316408{col 98}{space 3} .4950037
{txt}{space 40}49  {c |}{col 45}{res}{space 2} .4488898{col 57}{space 2} .1906132{col 68}{space 1}    2.35{col 77}{space 3}0.020{col 85}{space 4} .0708968{col 98}{space 3} .8268828
{txt}{space 40}50  {c |}{col 45}{res}{space 2} .4267681{col 57}{space 2} .1585916{col 68}{space 1}    2.69{col 77}{space 3}0.008{col 85}{space 4}  .112275{col 98}{space 3} .7412613
{txt}{space 40}51  {c |}{col 45}{res}{space 2} .3788337{col 57}{space 2} .1890666{col 68}{space 1}    2.00{col 77}{space 3}0.048{col 85}{space 4} .0039076{col 98}{space 3} .7537598
{txt}{space 40}52  {c |}{col 45}{res}{space 2} .3429612{col 57}{space 2} .1809789{col 68}{space 1}    1.90{col 77}{space 3}0.061{col 85}{space 4}-.0159268{col 98}{space 3} .7018492
{txt}{space 40}53  {c |}{col 45}{res}{space 2} .3055546{col 57}{space 2} .1342692{col 68}{space 1}    2.28{col 77}{space 3}0.025{col 85}{space 4} .0392938{col 98}{space 3} .5718155
{txt}{space 40}54  {c |}{col 45}{res}{space 2} .3483221{col 57}{space 2} .1521992{col 68}{space 1}    2.29{col 77}{space 3}0.024{col 85}{space 4} .0465054{col 98}{space 3} .6501388
{txt}{space 40}55  {c |}{col 45}{res}{space 2} .5436907{col 57}{space 2} .2121358{col 68}{space 1}    2.56{col 77}{space 3}0.012{col 85}{space 4} .1230174{col 98}{space 3}  .964364
{txt}{space 40}56  {c |}{col 45}{res}{space 2} .3027345{col 57}{space 2} .1980549{col 68}{space 1}    1.53{col 77}{space 3}0.129{col 85}{space 4}-.0900157{col 98}{space 3} .6954848
{txt}{space 40}57  {c |}{col 45}{res}{space 2} .4090223{col 57}{space 2} .2288685{col 68}{space 1}    1.79{col 77}{space 3}0.077{col 85}{space 4}-.0448325{col 98}{space 3}  .862877
{txt}{space 40}58  {c |}{col 45}{res}{space 2} .3023052{col 57}{space 2} .1500797{col 68}{space 1}    2.01{col 77}{space 3}0.047{col 85}{space 4} .0046915{col 98}{space 3}  .599919
{txt}{space 40}59  {c |}{col 45}{res}{space 2}  .344394{col 57}{space 2} .1698066{col 68}{space 1}    2.03{col 77}{space 3}0.045{col 85}{space 4} .0076612{col 98}{space 3} .6811268
{txt}{space 40}60  {c |}{col 45}{res}{space 2} .1852074{col 57}{space 2} .0928462{col 68}{space 1}    1.99{col 77}{space 3}0.049{col 85}{space 4} .0010898{col 98}{space 3} .3693249
{txt}{space 40}61  {c |}{col 45}{res}{space 2} .1891889{col 57}{space 2} .1060906{col 68}{space 1}    1.78{col 77}{space 3}0.077{col 85}{space 4}-.0211929{col 98}{space 3} .3995706
{txt}{space 40}62  {c |}{col 45}{res}{space 2} .4020137{col 57}{space 2} .1720794{col 68}{space 1}    2.34{col 77}{space 3}0.021{col 85}{space 4} .0607737{col 98}{space 3} .7432537
{txt}{space 40}63  {c |}{col 45}{res}{space 2} .4625887{col 57}{space 2} .1702621{col 68}{space 1}    2.72{col 77}{space 3}0.008{col 85}{space 4} .1249526{col 98}{space 3} .8002247
{txt}{space 40}64  {c |}{col 45}{res}{space 2} .4651807{col 57}{space 2} .1853862{col 68}{space 1}    2.51{col 77}{space 3}0.014{col 85}{space 4}  .097553{col 98}{space 3} .8328085
{txt}{space 40}65  {c |}{col 45}{res}{space 2} .2747193{col 57}{space 2} .1021637{col 68}{space 1}    2.69{col 77}{space 3}0.008{col 85}{space 4} .0721249{col 98}{space 3} .4773137
{txt}{space 40}66  {c |}{col 45}{res}{space 2} .3291135{col 57}{space 2} .2027356{col 68}{space 1}    1.62{col 77}{space 3}0.108{col 85}{space 4}-.0729187{col 98}{space 3} .7311458
{txt}{space 40}67  {c |}{col 45}{res}{space 2} .3330496{col 57}{space 2} .1312753{col 68}{space 1}    2.54{col 77}{space 3}0.013{col 85}{space 4} .0727257{col 98}{space 3} .5933735
{txt}{space 40}68  {c |}{col 45}{res}{space 2} .3207035{col 57}{space 2} .1481908{col 68}{space 1}    2.16{col 77}{space 3}0.033{col 85}{space 4} .0268355{col 98}{space 3} .6145716
{txt}{space 40}69  {c |}{col 45}{res}{space 2} .1984092{col 57}{space 2} .1137004{col 68}{space 1}    1.75{col 77}{space 3}0.084{col 85}{space 4}-.0270629{col 98}{space 3} .4238814
{txt}{space 40}70  {c |}{col 45}{res}{space 2} .4176728{col 57}{space 2} .1858256{col 68}{space 1}    2.25{col 77}{space 3}0.027{col 85}{space 4} .0491737{col 98}{space 3} .7861719
{txt}{space 40}71  {c |}{col 45}{res}{space 2} .1240967{col 57}{space 2} .1371027{col 68}{space 1}    0.91{col 77}{space 3}0.367{col 85}{space 4}-.1477831{col 98}{space 3} .3959764
{txt}{space 40}72  {c |}{col 45}{res}{space 2} .2788907{col 57}{space 2} .1114382{col 68}{space 1}    2.50{col 77}{space 3}0.014{col 85}{space 4} .0579044{col 98}{space 3} .4998769
{txt}{space 40}73  {c |}{col 45}{res}{space 2} .4973251{col 57}{space 2} .1677428{col 68}{space 1}    2.96{col 77}{space 3}0.004{col 85}{space 4} .1646849{col 98}{space 3} .8299654
{txt}{space 40}74  {c |}{col 45}{res}{space 2} .0985432{col 57}{space 2} .1079469{col 68}{space 1}    0.91{col 77}{space 3}0.363{col 85}{space 4}-.1155195{col 98}{space 3} .3126059
{txt}{space 40}75  {c |}{col 45}{res}{space 2} .1966837{col 57}{space 2} .1271073{col 68}{space 1}    1.55{col 77}{space 3}0.125{col 85}{space 4}-.0553748{col 98}{space 3} .4487422
{txt}{space 40}76  {c |}{col 45}{res}{space 2} .3398965{col 57}{space 2} .1526248{col 68}{space 1}    2.23{col 77}{space 3}0.028{col 85}{space 4} .0372358{col 98}{space 3} .6425573
{txt}{space 40}77  {c |}{col 45}{res}{space 2} .2688497{col 57}{space 2} .1447728{col 68}{space 1}    1.86{col 77}{space 3}0.066{col 85}{space 4}-.0182402{col 98}{space 3} .5559395
{txt}{space 40}78  {c |}{col 45}{res}{space 2} .2993839{col 57}{space 2} .0982708{col 68}{space 1}    3.05{col 77}{space 3}0.003{col 85}{space 4} .1045092{col 98}{space 3} .4942586
{txt}{space 40}79  {c |}{col 45}{res}{space 2}-.0137882{col 57}{space 2} .0162788{col 68}{space 1}   -0.85{col 77}{space 3}0.399{col 85}{space 4}-.0460697{col 98}{space 3} .0184934
{txt}{space 40}80  {c |}{col 45}{res}{space 2} .4389498{col 57}{space 2} .1715435{col 68}{space 1}    2.56{col 77}{space 3}0.012{col 85}{space 4} .0987726{col 98}{space 3} .7791269
{txt}{space 40}81  {c |}{col 45}{res}{space 2} .2187035{col 57}{space 2} .1764539{col 68}{space 1}    1.24{col 77}{space 3}0.218{col 85}{space 4}-.1312112{col 98}{space 3} .5686182
{txt}{space 40}82  {c |}{col 45}{res}{space 2} .3625055{col 57}{space 2} .1833054{col 68}{space 1}    1.98{col 77}{space 3}0.051{col 85}{space 4} -.000996{col 98}{space 3} .7260071
{txt}{space 40}83  {c |}{col 45}{res}{space 2} .4338925{col 57}{space 2} .1443817{col 68}{space 1}    3.01{col 77}{space 3}0.003{col 85}{space 4} .1475782{col 98}{space 3} .7202069
{txt}{space 40}84  {c |}{col 45}{res}{space 2} .3388557{col 57}{space 2} .1837444{col 68}{space 1}    1.84{col 77}{space 3}0.068{col 85}{space 4}-.0255163{col 98}{space 3} .7032277
{txt}{space 40}85  {c |}{col 45}{res}{space 2} .4089366{col 57}{space 2} .1460307{col 68}{space 1}    2.80{col 77}{space 3}0.006{col 85}{space 4} .1193521{col 98}{space 3}  .698521
{txt}{space 40}86  {c |}{col 45}{res}{space 2} .4709558{col 57}{space 2} .1885512{col 68}{space 1}    2.50{col 77}{space 3}0.014{col 85}{space 4} .0970517{col 98}{space 3} .8448599
{txt}{space 40}87  {c |}{col 45}{res}{space 2} .4738044{col 57}{space 2} .1893955{col 68}{space 1}    2.50{col 77}{space 3}0.014{col 85}{space 4} .0982261{col 98}{space 3} .8493827
{txt}{space 40}88  {c |}{col 45}{res}{space 2} .2588617{col 57}{space 2} .1340276{col 68}{space 1}    1.93{col 77}{space 3}0.056{col 85}{space 4}-.0069201{col 98}{space 3} .5246434
{txt}{space 40}89  {c |}{col 45}{res}{space 2} .3043544{col 57}{space 2} .1450428{col 68}{space 1}    2.10{col 77}{space 3}0.038{col 85}{space 4} .0167292{col 98}{space 3} .5919797
{txt}{space 40}90  {c |}{col 45}{res}{space 2}  .081169{col 57}{space 2} .1085114{col 68}{space 1}    0.75{col 77}{space 3}0.456{col 85}{space 4}-.1340131{col 98}{space 3}  .296351
{txt}{space 40}91  {c |}{col 45}{res}{space 2} .1980174{col 57}{space 2} .1089205{col 68}{space 1}    1.82{col 77}{space 3}0.072{col 85}{space 4}-.0179761{col 98}{space 3} .4140109
{txt}{space 40}92  {c |}{col 45}{res}{space 2} .0808868{col 57}{space 2} .0444754{col 68}{space 1}    1.82{col 77}{space 3}0.072{col 85}{space 4}-.0073095{col 98}{space 3} .1690831
{txt}{space 40}93  {c |}{col 45}{res}{space 2} .4337745{col 57}{space 2} .1454109{col 68}{space 1}    2.98{col 77}{space 3}0.004{col 85}{space 4} .1454194{col 98}{space 3} .7221297
{txt}{space 40}94  {c |}{col 45}{res}{space 2} .4690204{col 57}{space 2} .1652172{col 68}{space 1}    2.84{col 77}{space 3}0.005{col 85}{space 4} .1413885{col 98}{space 3} .7966523
{txt}{space 40}95  {c |}{col 45}{res}{space 2} .2211358{col 57}{space 2}   .14362{col 68}{space 1}    1.54{col 77}{space 3}0.127{col 85}{space 4}-.0636682{col 98}{space 3} .5059397
{txt}{space 40}96  {c |}{col 45}{res}{space 2} .3461993{col 57}{space 2}  .153137{col 68}{space 1}    2.26{col 77}{space 3}0.026{col 85}{space 4} .0425229{col 98}{space 3} .6498758
{txt}{space 40}97  {c |}{col 45}{res}{space 2} .4004625{col 57}{space 2} .1473922{col 68}{space 1}    2.72{col 77}{space 3}0.008{col 85}{space 4} .1081784{col 98}{space 3} .6927467
{txt}{space 40}98  {c |}{col 45}{res}{space 2} .5653575{col 57}{space 2} .1825899{col 68}{space 1}    3.10{col 77}{space 3}0.003{col 85}{space 4} .2032749{col 98}{space 3} .9274401
{txt}{space 40}99  {c |}{col 45}{res}{space 2} .0923688{col 57}{space 2} .0916173{col 68}{space 1}    1.01{col 77}{space 3}0.316{col 85}{space 4}-.0893117{col 98}{space 3} .2740493
{txt}{space 39}100  {c |}{col 45}{res}{space 2} .2561494{col 57}{space 2} .1472151{col 68}{space 1}    1.74{col 77}{space 3}0.085{col 85}{space 4}-.0357838{col 98}{space 3} .5480825
{txt}{space 39}101  {c |}{col 45}{res}{space 2}  .409054{col 57}{space 2} .1330802{col 68}{space 1}    3.07{col 77}{space 3}0.003{col 85}{space 4}  .145151{col 98}{space 3}  .672957
{txt}{space 39}102  {c |}{col 45}{res}{space 2} .2545856{col 57}{space 2}  .153153{col 68}{space 1}    1.66{col 77}{space 3}0.099{col 85}{space 4}-.0491225{col 98}{space 3} .5582938
{txt}{space 39}103  {c |}{col 45}{res}{space 2} .0757658{col 57}{space 2} .1045116{col 68}{space 1}    0.72{col 77}{space 3}0.470{col 85}{space 4}-.1314846{col 98}{space 3} .2830162
{txt}{space 39}104  {c |}{col 45}{res}{space 2}-.0999187{col 57}{space 2} .0751904{col 68}{space 1}   -1.33{col 77}{space 3}0.187{col 85}{space 4}-.2490241{col 98}{space 3} .0491867
{txt}{space 39}105  {c |}{col 45}{res}{space 2} .3399539{col 57}{space 2} .1514339{col 68}{space 1}    2.24{col 77}{space 3}0.027{col 85}{space 4} .0396547{col 98}{space 3} .6402531
{txt}{space 43} {c |}
{space 39}year {c |}
{space 38}2011  {c |}{col 45}{res}{space 2}-.0041404{col 57}{space 2} .0032444{col 68}{space 1}   -1.28{col 77}{space 3}0.205{col 85}{space 4}-.0105742{col 98}{space 3} .0022933
{txt}{space 38}2012  {c |}{col 45}{res}{space 2}-.0002999{col 57}{space 2} .0045584{col 68}{space 1}   -0.07{col 77}{space 3}0.948{col 85}{space 4}-.0093394{col 98}{space 3} .0087395
{txt}{space 38}2013  {c |}{col 45}{res}{space 2}-.0013709{col 57}{space 2} .0050859{col 68}{space 1}   -0.27{col 77}{space 3}0.788{col 85}{space 4}-.0114565{col 98}{space 3} .0087147
{txt}{space 38}2014  {c |}{col 45}{res}{space 2}-.0074111{col 57}{space 2} .0071549{col 68}{space 1}   -1.04{col 77}{space 3}0.303{col 85}{space 4}-.0215996{col 98}{space 3} .0067773
{txt}{space 38}2015  {c |}{col 45}{res}{space 2} -.014954{col 57}{space 2} .0086447{col 68}{space 1}   -1.73{col 77}{space 3}0.087{col 85}{space 4}-.0320968{col 98}{space 3} .0021888
{txt}{space 38}2016  {c |}{col 45}{res}{space 2}-.0182965{col 57}{space 2} .0074689{col 68}{space 1}   -2.45{col 77}{space 3}0.016{col 85}{space 4}-.0331076{col 98}{space 3}-.0034853
{txt}{space 38}2017  {c |}{col 45}{res}{space 2}-.0039276{col 57}{space 2} .0096293{col 68}{space 1}   -0.41{col 77}{space 3}0.684{col 85}{space 4}-.0230229{col 98}{space 3} .0151676
{txt}{space 38}2018  {c |}{col 45}{res}{space 2}-.0330958{col 57}{space 2} .0074304{col 68}{space 1}   -4.45{col 77}{space 3}0.000{col 85}{space 4}-.0478305{col 98}{space 3}-.0183611
{txt}{space 38}2019  {c |}{col 45}{res}{space 2}-.0713872{col 57}{space 2} .0084903{col 68}{space 1}   -8.41{col 77}{space 3}0.000{col 85}{space 4}-.0882237{col 98}{space 3}-.0545507
{txt}{space 43} {c |}
{space 38}_cons {c |}{col 45}{res}{space 2}-.1481017{col 57}{space 2}  .412299{col 68}{space 1}   -0.36{col 77}{space 3}0.720{col 85}{space 4} -.965706{col 98}{space 3} .6695026
{txt}{hline 44}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1890910{col 50}    25{col 58}  3781870{col 69}  3782188
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1357575{col 26}{space 2} .0450905{col 37}{space 1}    3.01{col 46}{space 3}0.003{col 54}{space 4} .0463414{col 67}{space 3} .2251736
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0011512{col 26}{space 2} .0281804{col 37}{space 1}    0.04{col 46}{space 3}0.967{col 54}{space 4}-.0547317{col 67}{space 3}  .057034
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0241578{col 26}{space 2} .0284199{col 37}{space 1}    0.85{col 46}{space 3}0.397{col 54}{space 4}-.0321998{col 67}{space 3} .0805155
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom 2.women_het#c.ln_ratio_fmsup_fmsub -  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0230067{col 26}{space 2} .0192755{col 37}{space 1}    1.19{col 46}{space 3}0.235{col 54}{space 4}-.0152174{col 67}{space 3} .0612307
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT:BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEENGENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1934972{col 26}{space 2} .0481252{col 37}{space 1}    4.02{col 46}{space 3}0.000{col 54}{space 4} .0980632{col 67}{space 3} .2889313
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub + 1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0076171{col 26}{space 2} .0157336{col 37}{space 1}    0.48{col 46}{space 3}0.629{col 54}{space 4}-.0235833{col 67}{space 3} .0388174
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0032866{col 26}{space 2} .0340386{col 37}{space 1}   -0.10{col 46}{space 3}0.923{col 54}{space 4}-.0707863{col 67}{space 3} .0642132
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub - (1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub - 1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub + 2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0109037{col 26}{space 2} .0303533{col 37}{space 1}   -0.36{col 46}{space 3}0.720{col 54}{space 4}-.0710955{col 67}{space 3} .0492882
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG WOMEN RESPONDENT DIFFERENCES [NON-MINORITY WOMEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub  - (1.women_het#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0064659{col 26}{space 2}  .029295{col 37}{space 1}    0.22{col 46}{space 3}0.826{col 54}{space 4}-.0516271{col 67}{space 3} .0645589
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub  - (2.women_het#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0274444{col 26}{space 2}  .039576{col 37}{space 1}   -0.69{col 46}{space 3}0.490{col 54}{space 4} -.105925{col 67}{space 3} .0510362
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
.    
. *** MODEL 8: CONDITIONAL RESPONSES BY RACE/ETHNICITY & POSITION -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL  ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority_het##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year if e(sample), vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(24, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0406
                                                {txt}Root MSE          =    {res} .51447

{txt}{ralign 114:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 49}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 50}{c |}{col 62}    Robust
{col 1}                             lndiversity2zeroadj{col 50}{c |} Coefficient{col 62}  std. err.{col 74}      t{col 82}   P>|t|{col 90}     [95% con{col 103}f. interval]
{hline 49}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 26}ln_ratio_mnmsup_mnmsub {c |}{col 50}{res}{space 2} .0509063{col 62}{space 2} .0341925{col 73}{space 1}    1.49{col 82}{space 3}0.140{col 90}{space 4}-.0168988{col 103}{space 3} .1187113
{txt}{space 48} {c |}
{space 36}minority_het {c |}
{space 46}1  {c |}{col 50}{res}{space 2}-.0712726{col 62}{space 2}  .006072{col 73}{space 1}  -11.74{col 82}{space 3}0.000{col 90}{space 4}-.0833136{col 103}{space 3}-.0592315
{txt}{space 46}2  {c |}{col 50}{res}{space 2} -.097107{col 62}{space 2} .0085713{col 73}{space 1}  -11.33{col 82}{space 3}0.000{col 90}{space 4}-.1141042{col 103}{space 3}-.0801099
{txt}{space 48} {c |}
{space 11}minority_het#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0152207{col 62}{space 2} .0167619{col 73}{space 1}    0.91{col 82}{space 3}0.366{col 90}{space 4}-.0180187{col 103}{space 3} .0484602
{txt}{space 46}2  {c |}{col 50}{res}{space 2} .0524324{col 62}{space 2} .0216625{col 73}{space 1}    2.42{col 82}{space 3}0.017{col 90}{space 4} .0094749{col 103}{space 3} .0953899
{txt}{space 48} {c |}
{space 36}1.supervisor {c |}{col 50}{res}{space 2} .1298839{col 62}{space 2} .0137199{col 73}{space 1}    9.47{col 82}{space 3}0.000{col 90}{space 4} .1026768{col 103}{space 3} .1570911
{txt}{space 48} {c |}
{space 13}supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0104996{col 62}{space 2} .0271214{col 73}{space 1}    0.39{col 82}{space 3}0.699{col 90}{space 4}-.0432831{col 103}{space 3} .0642823
{txt}{space 48} {c |}
{space 25}minority_het#supervisor {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0140678{col 62}{space 2} .0090803{col 73}{space 1}    1.55{col 82}{space 3}0.124{col 90}{space 4}-.0039388{col 103}{space 3} .0320743
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2} .0156061{col 62}{space 2}  .015225{col 73}{space 1}    1.03{col 82}{space 3}0.308{col 90}{space 4}-.0145856{col 103}{space 3} .0457979
{txt}{space 48} {c |}
minority_het#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0512005{col 62}{space 2} .0191157{col 73}{space 1}    2.68{col 82}{space 3}0.009{col 90}{space 4} .0132933{col 103}{space 3} .0891076
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2} .0141057{col 62}{space 2} .0297025{col 73}{space 1}    0.47{col 82}{space 3}0.636{col 90}{space 4}-.0447955{col 103}{space 3} .0730069
{txt}{space 48} {c |}
{space 23}ln_ratio_min_tot_nmin_tot {c |}{col 50}{res}{space 2}  .053853{col 62}{space 2} .0451325{col 73}{space 1}    1.19{col 82}{space 3}0.235{col 90}{space 4}-.0356465{col 103}{space 3} .1433525
{txt}{space 42}gender {c |}{col 50}{res}{space 2}-.0270464{col 62}{space 2}  .004458{col 73}{space 1}   -6.07{col 82}{space 3}0.000{col 90}{space 4}-.0358868{col 103}{space 3} -.018206
{txt}{space 32}topoffminority_2 {c |}{col 50}{res}{space 2} .0074957{col 62}{space 2} .0059284{col 73}{space 1}    1.26{col 82}{space 3}0.209{col 90}{space 4}-.0042605{col 103}{space 3} .0192518
{txt}{space 28}lntotworkforce_count {c |}{col 50}{res}{space 2} .0647489{col 62}{space 2} .0402335{col 73}{space 1}    1.61{col 82}{space 3}0.111{col 90}{space 4}-.0150357{col 103}{space 3} .1445335
{txt}{space 20}ln_professionals_total_ratio {c |}{col 50}{res}{space 2} .0220077{col 62}{space 2} .0501638{col 73}{space 1}    0.44{col 82}{space 3}0.662{col 90}{space 4}-.0774689{col 103}{space 3} .1214844
{txt}{space 48} {c |}
{space 40}agencyid {c |}
{space 46}2  {c |}{col 50}{res}{space 2} .2107772{col 62}{space 2} .1224839{col 73}{space 1}    1.72{col 82}{space 3}0.088{col 90}{space 4} -.032113{col 103}{space 3} .4536674
{txt}{space 46}3  {c |}{col 50}{res}{space 2} .0312795{col 62}{space 2} .0542472{col 73}{space 1}    0.58{col 82}{space 3}0.565{col 90}{space 4}-.0762947{col 103}{space 3} .1388537
{txt}{space 46}4  {c |}{col 50}{res}{space 2} .2816698{col 62}{space 2} .1639402{col 73}{space 1}    1.72{col 82}{space 3}0.089{col 90}{space 4}-.0434297{col 103}{space 3} .6067693
{txt}{space 46}5  {c |}{col 50}{res}{space 2} .1675275{col 62}{space 2} .1273086{col 73}{space 1}    1.32{col 82}{space 3}0.191{col 90}{space 4}-.0849302{col 103}{space 3} .4199851
{txt}{space 46}6  {c |}{col 50}{res}{space 2} .1716153{col 62}{space 2} .1185313{col 73}{space 1}    1.45{col 82}{space 3}0.151{col 90}{space 4}-.0634368{col 103}{space 3} .4066673
{txt}{space 46}7  {c |}{col 50}{res}{space 2} .2441548{col 62}{space 2} .2172326{col 73}{space 1}    1.12{col 82}{space 3}0.264{col 90}{space 4}-.1866256{col 103}{space 3} .6749353
{txt}{space 46}8  {c |}{col 50}{res}{space 2} .2331087{col 62}{space 2} .1622444{col 73}{space 1}    1.44{col 82}{space 3}0.154{col 90}{space 4} -.088628{col 103}{space 3} .5548455
{txt}{space 46}9  {c |}{col 50}{res}{space 2}-.0558148{col 62}{space 2} .0229621{col 73}{space 1}   -2.43{col 82}{space 3}0.017{col 90}{space 4}-.1013496{col 103}{space 3}  -.01028
{txt}{space 45}10  {c |}{col 50}{res}{space 2} .1887588{col 62}{space 2} .2310985{col 73}{space 1}    0.82{col 82}{space 3}0.416{col 90}{space 4}-.2695183{col 103}{space 3} .6470359
{txt}{space 45}11  {c |}{col 50}{res}{space 2} .1586759{col 62}{space 2} .1049406{col 73}{space 1}    1.51{col 82}{space 3}0.134{col 90}{space 4}-.0494251{col 103}{space 3}  .366777
{txt}{space 45}12  {c |}{col 50}{res}{space 2}   .31636{col 62}{space 2} .2144414{col 73}{space 1}    1.48{col 82}{space 3}0.143{col 90}{space 4}-.1088854{col 103}{space 3} .7416053
{txt}{space 45}13  {c |}{col 50}{res}{space 2} .3128464{col 62}{space 2} .1625261{col 73}{space 1}    1.92{col 82}{space 3}0.057{col 90}{space 4}-.0094489{col 103}{space 3} .6351416
{txt}{space 45}14  {c |}{col 50}{res}{space 2}  .156533{col 62}{space 2} .1099676{col 73}{space 1}    1.42{col 82}{space 3}0.158{col 90}{space 4}-.0615368{col 103}{space 3} .3746029
{txt}{space 45}15  {c |}{col 50}{res}{space 2} .2316051{col 62}{space 2} .1541758{col 73}{space 1}    1.50{col 82}{space 3}0.136{col 90}{space 4}-.0741312{col 103}{space 3} .5373414
{txt}{space 45}16  {c |}{col 50}{res}{space 2} .2037202{col 62}{space 2} .2878734{col 73}{space 1}    0.71{col 82}{space 3}0.481{col 90}{space 4}-.3671436{col 103}{space 3}  .774584
{txt}{space 45}17  {c |}{col 50}{res}{space 2}  .044901{col 62}{space 2}  .187766{col 73}{space 1}    0.24{col 82}{space 3}0.811{col 90}{space 4}-.3274461{col 103}{space 3} .4172481
{txt}{space 45}18  {c |}{col 50}{res}{space 2}  .307025{col 62}{space 2} .1691813{col 73}{space 1}    1.81{col 82}{space 3}0.072{col 90}{space 4}-.0284678{col 103}{space 3} .6425178
{txt}{space 45}19  {c |}{col 50}{res}{space 2} .1786883{col 62}{space 2} .1143956{col 73}{space 1}    1.56{col 82}{space 3}0.121{col 90}{space 4}-.0481624{col 103}{space 3} .4055391
{txt}{space 45}20  {c |}{col 50}{res}{space 2} .0582686{col 62}{space 2} .1201657{col 73}{space 1}    0.48{col 82}{space 3}0.629{col 90}{space 4}-.1800244{col 103}{space 3} .2965617
{txt}{space 45}21  {c |}{col 50}{res}{space 2} .2104368{col 62}{space 2} .1096497{col 73}{space 1}    1.92{col 82}{space 3}0.058{col 90}{space 4}-.0070027{col 103}{space 3} .4278762
{txt}{space 45}22  {c |}{col 50}{res}{space 2} .1467558{col 62}{space 2} .1737155{col 73}{space 1}    0.84{col 82}{space 3}0.400{col 90}{space 4}-.1977284{col 103}{space 3} .4912401
{txt}{space 45}23  {c |}{col 50}{res}{space 2}-.1051139{col 62}{space 2} .0878521{col 73}{space 1}   -1.20{col 82}{space 3}0.234{col 90}{space 4}-.2793279{col 103}{space 3} .0691001
{txt}{space 45}24  {c |}{col 50}{res}{space 2} .2473779{col 62}{space 2} .1222408{col 73}{space 1}    2.02{col 82}{space 3}0.046{col 90}{space 4} .0049698{col 103}{space 3}  .489786
{txt}{space 45}25  {c |}{col 50}{res}{space 2}  .188433{col 62}{space 2} .1486244{col 73}{space 1}    1.27{col 82}{space 3}0.208{col 90}{space 4}-.1062949{col 103}{space 3} .4831608
{txt}{space 45}26  {c |}{col 50}{res}{space 2} .0511884{col 62}{space 2} .1314538{col 73}{space 1}    0.39{col 82}{space 3}0.698{col 90}{space 4}-.2094894{col 103}{space 3} .3118663
{txt}{space 45}27  {c |}{col 50}{res}{space 2} .3568372{col 62}{space 2} .1969992{col 73}{space 1}    1.81{col 82}{space 3}0.073{col 90}{space 4}-.0338197{col 103}{space 3}  .747494
{txt}{space 45}28  {c |}{col 50}{res}{space 2}-.0506198{col 62}{space 2}  .111556{col 73}{space 1}   -0.45{col 82}{space 3}0.651{col 90}{space 4}-.2718394{col 103}{space 3} .1705999
{txt}{space 45}29  {c |}{col 50}{res}{space 2} .0791208{col 62}{space 2}  .187437{col 73}{space 1}    0.42{col 82}{space 3}0.674{col 90}{space 4}-.2925738{col 103}{space 3} .4508154
{txt}{space 45}30  {c |}{col 50}{res}{space 2} .1605569{col 62}{space 2} .1733251{col 73}{space 1}    0.93{col 82}{space 3}0.356{col 90}{space 4}-.1831533{col 103}{space 3} .5042671
{txt}{space 45}31  {c |}{col 50}{res}{space 2}-.0204104{col 62}{space 2} .1790103{col 73}{space 1}   -0.11{col 82}{space 3}0.909{col 90}{space 4}-.3753946{col 103}{space 3} .3345738
{txt}{space 45}32  {c |}{col 50}{res}{space 2} .2045952{col 62}{space 2} .1423254{col 73}{space 1}    1.44{col 82}{space 3}0.154{col 90}{space 4}-.0776414{col 103}{space 3} .4868319
{txt}{space 45}33  {c |}{col 50}{res}{space 2} .1186208{col 62}{space 2} .0895597{col 73}{space 1}    1.32{col 82}{space 3}0.188{col 90}{space 4}-.0589795{col 103}{space 3} .2962211
{txt}{space 45}34  {c |}{col 50}{res}{space 2}-.1482254{col 62}{space 2}   .22731{col 73}{space 1}   -0.65{col 82}{space 3}0.516{col 90}{space 4}-.5989896{col 103}{space 3} .3025389
{txt}{space 45}35  {c |}{col 50}{res}{space 2} .1391809{col 62}{space 2} .1023799{col 73}{space 1}    1.36{col 82}{space 3}0.177{col 90}{space 4}-.0638422{col 103}{space 3}  .342204
{txt}{space 45}36  {c |}{col 50}{res}{space 2} .2118911{col 62}{space 2}   .13506{col 73}{space 1}    1.57{col 82}{space 3}0.120{col 90}{space 4}-.0559379{col 103}{space 3} .4797201
{txt}{space 45}37  {c |}{col 50}{res}{space 2} .1961422{col 62}{space 2}  .114941{col 73}{space 1}    1.71{col 82}{space 3}0.091{col 90}{space 4}-.0317901{col 103}{space 3} .4240746
{txt}{space 45}38  {c |}{col 50}{res}{space 2} .3092775{col 62}{space 2} .1961006{col 73}{space 1}    1.58{col 82}{space 3}0.118{col 90}{space 4}-.0795974{col 103}{space 3} .6981524
{txt}{space 45}39  {c |}{col 50}{res}{space 2} .2154465{col 62}{space 2} .1177374{col 73}{space 1}    1.83{col 82}{space 3}0.070{col 90}{space 4}-.0180311{col 103}{space 3} .4489241
{txt}{space 45}40  {c |}{col 50}{res}{space 2} .0423224{col 62}{space 2} .0782475{col 73}{space 1}    0.54{col 82}{space 3}0.590{col 90}{space 4}-.1128453{col 103}{space 3}   .19749
{txt}{space 45}41  {c |}{col 50}{res}{space 2} .1824122{col 62}{space 2} .1717568{col 73}{space 1}    1.06{col 82}{space 3}0.291{col 90}{space 4}-.1581881{col 103}{space 3} .5230124
{txt}{space 45}42  {c |}{col 50}{res}{space 2} .2194493{col 62}{space 2} .1606624{col 73}{space 1}    1.37{col 82}{space 3}0.175{col 90}{space 4}-.0991503{col 103}{space 3} .5380489
{txt}{space 45}43  {c |}{col 50}{res}{space 2}  .005861{col 62}{space 2} .0739633{col 73}{space 1}    0.08{col 82}{space 3}0.937{col 90}{space 4}-.1408109{col 103}{space 3} .1525329
{txt}{space 45}44  {c |}{col 50}{res}{space 2} .2577755{col 62}{space 2}  .137156{col 73}{space 1}    1.88{col 82}{space 3}0.063{col 90}{space 4}-.0142101{col 103}{space 3}  .529761
{txt}{space 45}45  {c |}{col 50}{res}{space 2}  .219378{col 62}{space 2} .1204046{col 73}{space 1}    1.82{col 82}{space 3}0.071{col 90}{space 4}-.0193889{col 103}{space 3}  .458145
{txt}{space 45}46  {c |}{col 50}{res}{space 2} .1265445{col 62}{space 2} .2121691{col 73}{space 1}    0.60{col 82}{space 3}0.552{col 90}{space 4}-.2941948{col 103}{space 3} .5472838
{txt}{space 45}47  {c |}{col 50}{res}{space 2} .1533326{col 62}{space 2} .0923599{col 73}{space 1}    1.66{col 82}{space 3}0.100{col 90}{space 4}-.0298206{col 103}{space 3} .3364857
{txt}{space 45}48  {c |}{col 50}{res}{space 2} .2388012{col 62}{space 2} .1888159{col 73}{space 1}    1.26{col 82}{space 3}0.209{col 90}{space 4}-.1356278{col 103}{space 3} .6132302
{txt}{space 45}49  {c |}{col 50}{res}{space 2} .3309391{col 62}{space 2} .2043816{col 73}{space 1}    1.62{col 82}{space 3}0.108{col 90}{space 4}-.0743572{col 103}{space 3} .7362354
{txt}{space 45}50  {c |}{col 50}{res}{space 2} .3435947{col 62}{space 2} .1845788{col 73}{space 1}    1.86{col 82}{space 3}0.065{col 90}{space 4}-.0224319{col 103}{space 3} .7096213
{txt}{space 45}51  {c |}{col 50}{res}{space 2} .3368202{col 62}{space 2} .2318089{col 73}{space 1}    1.45{col 82}{space 3}0.149{col 90}{space 4}-.1228656{col 103}{space 3}  .796506
{txt}{space 45}52  {c |}{col 50}{res}{space 2} .2358258{col 62}{space 2} .2313733{col 73}{space 1}    1.02{col 82}{space 3}0.310{col 90}{space 4}-.2229961{col 103}{space 3} .6946477
{txt}{space 45}53  {c |}{col 50}{res}{space 2} .2723517{col 62}{space 2} .1662686{col 73}{space 1}    1.64{col 82}{space 3}0.104{col 90}{space 4}-.0573651{col 103}{space 3} .6020685
{txt}{space 45}54  {c |}{col 50}{res}{space 2} .2903409{col 62}{space 2} .1842003{col 73}{space 1}    1.58{col 82}{space 3}0.118{col 90}{space 4}-.0749352{col 103}{space 3} .6556171
{txt}{space 45}55  {c |}{col 50}{res}{space 2} .4149745{col 62}{space 2} .2353611{col 73}{space 1}    1.76{col 82}{space 3}0.081{col 90}{space 4}-.0517554{col 103}{space 3} .8817043
{txt}{space 45}56  {c |}{col 50}{res}{space 2} .2467435{col 62}{space 2}  .241104{col 73}{space 1}    1.02{col 82}{space 3}0.308{col 90}{space 4}-.2313748{col 103}{space 3} .7248617
{txt}{space 45}57  {c |}{col 50}{res}{space 2} .3157645{col 62}{space 2} .3038174{col 73}{space 1}    1.04{col 82}{space 3}0.301{col 90}{space 4}-.2867167{col 103}{space 3} .9182458
{txt}{space 45}58  {c |}{col 50}{res}{space 2} .1979419{col 62}{space 2} .1744495{col 73}{space 1}    1.13{col 82}{space 3}0.259{col 90}{space 4} -.147998{col 103}{space 3} .5438817
{txt}{space 45}59  {c |}{col 50}{res}{space 2} .1960186{col 62}{space 2} .2090951{col 73}{space 1}    0.94{col 82}{space 3}0.351{col 90}{space 4}-.2186248{col 103}{space 3}  .610662
{txt}{space 45}60  {c |}{col 50}{res}{space 2} .1439141{col 62}{space 2} .1035482{col 73}{space 1}    1.39{col 82}{space 3}0.168{col 90}{space 4}-.0614258{col 103}{space 3} .3492541
{txt}{space 45}61  {c |}{col 50}{res}{space 2} .1356793{col 62}{space 2} .1104993{col 73}{space 1}    1.23{col 82}{space 3}0.222{col 90}{space 4}-.0834449{col 103}{space 3} .3548034
{txt}{space 45}62  {c |}{col 50}{res}{space 2} .3193605{col 62}{space 2} .2067217{col 73}{space 1}    1.54{col 82}{space 3}0.125{col 90}{space 4}-.0905763{col 103}{space 3} .7292973
{txt}{space 45}63  {c |}{col 50}{res}{space 2} .3888716{col 62}{space 2} .2011707{col 73}{space 1}    1.93{col 82}{space 3}0.056{col 90}{space 4}-.0100575{col 103}{space 3} .7878008
{txt}{space 45}64  {c |}{col 50}{res}{space 2} .3995151{col 62}{space 2} .2110096{col 73}{space 1}    1.89{col 82}{space 3}0.061{col 90}{space 4}-.0189249{col 103}{space 3}  .817955
{txt}{space 45}65  {c |}{col 50}{res}{space 2} .2117707{col 62}{space 2}  .121341{col 73}{space 1}    1.75{col 82}{space 3}0.084{col 90}{space 4}-.0288531{col 103}{space 3} .4523944
{txt}{space 45}66  {c |}{col 50}{res}{space 2} .1907321{col 62}{space 2} .2237069{col 73}{space 1}    0.85{col 82}{space 3}0.396{col 90}{space 4}-.2528871{col 103}{space 3} .6343513
{txt}{space 45}67  {c |}{col 50}{res}{space 2}  .222125{col 62}{space 2}  .136879{col 73}{space 1}    1.62{col 82}{space 3}0.108{col 90}{space 4}-.0493112{col 103}{space 3} .4935612
{txt}{space 45}68  {c |}{col 50}{res}{space 2} .2796833{col 62}{space 2} .1526789{col 73}{space 1}    1.83{col 82}{space 3}0.070{col 90}{space 4}-.0230846{col 103}{space 3} .5824513
{txt}{space 45}69  {c |}{col 50}{res}{space 2} .1405823{col 62}{space 2} .1227151{col 73}{space 1}    1.15{col 82}{space 3}0.255{col 90}{space 4}-.1027664{col 103}{space 3} .3839309
{txt}{space 45}70  {c |}{col 50}{res}{space 2} .3489534{col 62}{space 2} .2108629{col 73}{space 1}    1.65{col 82}{space 3}0.101{col 90}{space 4}-.0691956{col 103}{space 3} .7671023
{txt}{space 45}71  {c |}{col 50}{res}{space 2}-.1056007{col 62}{space 2} .1816458{col 73}{space 1}   -0.58{col 82}{space 3}0.562{col 90}{space 4}-.4658111{col 103}{space 3} .2546096
{txt}{space 45}72  {c |}{col 50}{res}{space 2} .1995847{col 62}{space 2} .1184535{col 73}{space 1}    1.68{col 82}{space 3}0.095{col 90}{space 4}-.0353131{col 103}{space 3} .4344824
{txt}{space 45}73  {c |}{col 50}{res}{space 2} .4234289{col 62}{space 2} .1922247{col 73}{space 1}    2.20{col 82}{space 3}0.030{col 90}{space 4} .0422401{col 103}{space 3} .8046176
{txt}{space 45}74  {c |}{col 50}{res}{space 2} .1510367{col 62}{space 2} .1023547{col 73}{space 1}    1.48{col 82}{space 3}0.143{col 90}{space 4}-.0519365{col 103}{space 3} .3540099
{txt}{space 45}75  {c |}{col 50}{res}{space 2} .0692588{col 62}{space 2} .1504608{col 73}{space 1}    0.46{col 82}{space 3}0.646{col 90}{space 4}-.2291106{col 103}{space 3} .3676282
{txt}{space 45}76  {c |}{col 50}{res}{space 2} .2935975{col 62}{space 2} .1726293{col 73}{space 1}    1.70{col 82}{space 3}0.092{col 90}{space 4}-.0487329{col 103}{space 3} .6359278
{txt}{space 45}77  {c |}{col 50}{res}{space 2} .2198621{col 62}{space 2} .1712886{col 73}{space 1}    1.28{col 82}{space 3}0.202{col 90}{space 4}-.1198096{col 103}{space 3} .5595338
{txt}{space 45}78  {c |}{col 50}{res}{space 2} .2687533{col 62}{space 2} .1092894{col 73}{space 1}    2.46{col 82}{space 3}0.016{col 90}{space 4} .0520284{col 103}{space 3} .4854782
{txt}{space 45}79  {c |}{col 50}{res}{space 2}-.0171751{col 62}{space 2} .0254008{col 73}{space 1}   -0.68{col 82}{space 3}0.500{col 90}{space 4}-.0675458{col 103}{space 3} .0331955
{txt}{space 45}80  {c |}{col 50}{res}{space 2} .4324021{col 62}{space 2} .2177098{col 73}{space 1}    1.99{col 82}{space 3}0.050{col 90}{space 4} .0006755{col 103}{space 3} .8641288
{txt}{space 45}81  {c |}{col 50}{res}{space 2}  .154784{col 62}{space 2} .2385387{col 73}{space 1}    0.65{col 82}{space 3}0.518{col 90}{space 4}-.3182472{col 103}{space 3} .6278152
{txt}{space 45}82  {c |}{col 50}{res}{space 2} .2345272{col 62}{space 2} .2041528{col 73}{space 1}    1.15{col 82}{space 3}0.253{col 90}{space 4}-.1703155{col 103}{space 3} .6393699
{txt}{space 45}83  {c |}{col 50}{res}{space 2} .3428761{col 62}{space 2} .1690483{col 73}{space 1}    2.03{col 82}{space 3}0.045{col 90}{space 4} .0076469{col 103}{space 3} .6781053
{txt}{space 45}84  {c |}{col 50}{res}{space 2} .2856294{col 62}{space 2} .2073027{col 73}{space 1}    1.38{col 82}{space 3}0.171{col 90}{space 4}-.1254596{col 103}{space 3} .6967184
{txt}{space 45}85  {c |}{col 50}{res}{space 2} .3043471{col 62}{space 2} .1611465{col 73}{space 1}    1.89{col 82}{space 3}0.062{col 90}{space 4}-.0152125{col 103}{space 3} .6239067
{txt}{space 45}86  {c |}{col 50}{res}{space 2} .3274925{col 62}{space 2} .2402842{col 73}{space 1}    1.36{col 82}{space 3}0.176{col 90}{space 4}-.1490001{col 103}{space 3} .8039852
{txt}{space 45}87  {c |}{col 50}{res}{space 2}  .382853{col 62}{space 2} .2403632{col 73}{space 1}    1.59{col 82}{space 3}0.114{col 90}{space 4}-.0937963{col 103}{space 3} .8595023
{txt}{space 45}88  {c |}{col 50}{res}{space 2} .1693457{col 62}{space 2} .1689904{col 73}{space 1}    1.00{col 82}{space 3}0.319{col 90}{space 4}-.1657687{col 103}{space 3} .5044601
{txt}{space 45}89  {c |}{col 50}{res}{space 2} .2282469{col 62}{space 2} .1642635{col 73}{space 1}    1.39{col 82}{space 3}0.168{col 90}{space 4}-.0974937{col 103}{space 3} .5539876
{txt}{space 45}90  {c |}{col 50}{res}{space 2}  .020952{col 62}{space 2} .0838354{col 73}{space 1}    0.25{col 82}{space 3}0.803{col 90}{space 4}-.1452968{col 103}{space 3} .1872007
{txt}{space 45}91  {c |}{col 50}{res}{space 2} .1414072{col 62}{space 2} .1181098{col 73}{space 1}    1.20{col 82}{space 3}0.234{col 90}{space 4}-.0928088{col 103}{space 3} .3756233
{txt}{space 45}92  {c |}{col 50}{res}{space 2} .0816268{col 62}{space 2} .0597461{col 73}{space 1}    1.37{col 82}{space 3}0.175{col 90}{space 4}-.0368519{col 103}{space 3} .2001055
{txt}{space 45}93  {c |}{col 50}{res}{space 2}  .353337{col 62}{space 2}  .173007{col 73}{space 1}    2.04{col 82}{space 3}0.044{col 90}{space 4} .0102577{col 103}{space 3} .6964163
{txt}{space 45}94  {c |}{col 50}{res}{space 2} .4496433{col 62}{space 2} .2122127{col 73}{space 1}    2.12{col 82}{space 3}0.036{col 90}{space 4} .0288176{col 103}{space 3} .8704691
{txt}{space 45}95  {c |}{col 50}{res}{space 2} .1685851{col 62}{space 2} .2082581{col 73}{space 1}    0.81{col 82}{space 3}0.420{col 90}{space 4}-.2443985{col 103}{space 3} .5815687
{txt}{space 45}96  {c |}{col 50}{res}{space 2} .2937632{col 62}{space 2} .1882751{col 73}{space 1}    1.56{col 82}{space 3}0.122{col 90}{space 4}-.0795933{col 103}{space 3} .6671197
{txt}{space 45}97  {c |}{col 50}{res}{space 2} .3305298{col 62}{space 2} .1539318{col 73}{space 1}    2.15{col 82}{space 3}0.034{col 90}{space 4} .0252772{col 103}{space 3} .6357825
{txt}{space 45}98  {c |}{col 50}{res}{space 2} .4416959{col 62}{space 2} .2216201{col 73}{space 1}    1.99{col 82}{space 3}0.049{col 90}{space 4} .0022149{col 103}{space 3} .8811769
{txt}{space 45}99  {c |}{col 50}{res}{space 2} .0442682{col 62}{space 2} .0560718{col 73}{space 1}    0.79{col 82}{space 3}0.432{col 90}{space 4}-.0669242{col 103}{space 3} .1554606
{txt}{space 44}100  {c |}{col 50}{res}{space 2} .2083807{col 62}{space 2} .2103297{col 73}{space 1}    0.99{col 82}{space 3}0.324{col 90}{space 4}-.2087111{col 103}{space 3} .6254725
{txt}{space 44}101  {c |}{col 50}{res}{space 2} .3668895{col 62}{space 2} .1666614{col 73}{space 1}    2.20{col 82}{space 3}0.030{col 90}{space 4} .0363938{col 103}{space 3} .6973853
{txt}{space 44}102  {c |}{col 50}{res}{space 2} .2771062{col 62}{space 2} .2137076{col 73}{space 1}    1.30{col 82}{space 3}0.198{col 90}{space 4}-.1466839{col 103}{space 3} .7008963
{txt}{space 44}103  {c |}{col 50}{res}{space 2} .0796007{col 62}{space 2} .1172527{col 73}{space 1}    0.68{col 82}{space 3}0.499{col 90}{space 4}-.1529158{col 103}{space 3} .3121172
{txt}{space 44}104  {c |}{col 50}{res}{space 2}-.1600923{col 62}{space 2} .0603342{col 73}{space 1}   -2.65{col 82}{space 3}0.009{col 90}{space 4}-.2797372{col 103}{space 3}-.0404473
{txt}{space 44}105  {c |}{col 50}{res}{space 2} .2273085{col 62}{space 2} .1995005{col 73}{space 1}    1.14{col 82}{space 3}0.257{col 90}{space 4}-.1683084{col 103}{space 3} .6229253
{txt}{space 48} {c |}
{space 44}year {c |}
{space 43}2011  {c |}{col 50}{res}{space 2}-.0023752{col 62}{space 2} .0037701{col 73}{space 1}   -0.63{col 82}{space 3}0.530{col 90}{space 4}-.0098514{col 103}{space 3}  .005101
{txt}{space 43}2012  {c |}{col 50}{res}{space 2} .0045505{col 62}{space 2}  .004527{col 73}{space 1}    1.01{col 82}{space 3}0.317{col 90}{space 4}-.0044266{col 103}{space 3} .0135277
{txt}{space 43}2013  {c |}{col 50}{res}{space 2} .0026243{col 62}{space 2} .0056355{col 73}{space 1}    0.47{col 82}{space 3}0.642{col 90}{space 4}-.0085511{col 103}{space 3} .0137998
{txt}{space 43}2014  {c |}{col 50}{res}{space 2}-.0024277{col 62}{space 2} .0066023{col 73}{space 1}   -0.37{col 82}{space 3}0.714{col 90}{space 4}-.0155202{col 103}{space 3} .0106649
{txt}{space 43}2015  {c |}{col 50}{res}{space 2}-.0102865{col 62}{space 2} .0079982{col 73}{space 1}   -1.29{col 82}{space 3}0.201{col 90}{space 4}-.0261471{col 103}{space 3} .0055742
{txt}{space 43}2016  {c |}{col 50}{res}{space 2}-.0133032{col 62}{space 2} .0079767{col 73}{space 1}   -1.67{col 82}{space 3}0.098{col 90}{space 4}-.0291213{col 103}{space 3} .0025149
{txt}{space 43}2017  {c |}{col 50}{res}{space 2}-.0030056{col 62}{space 2} .0118105{col 73}{space 1}   -0.25{col 82}{space 3}0.800{col 90}{space 4}-.0264263{col 103}{space 3} .0204151
{txt}{space 43}2018  {c |}{col 50}{res}{space 2}-.0294437{col 62}{space 2} .0107722{col 73}{space 1}   -2.73{col 82}{space 3}0.007{col 90}{space 4}-.0508055{col 103}{space 3}-.0080819
{txt}{space 43}2019  {c |}{col 50}{res}{space 2}-.0685989{col 62}{space 2} .0121599{col 73}{space 1}   -5.64{col 82}{space 3}0.000{col 90}{space 4}-.0927124{col 103}{space 3}-.0444855
{txt}{space 48} {c |}
{space 43}_cons {c |}{col 50}{res}{space 2} .0421075{col 62}{space 2} .5063518{col 73}{space 1}    0.08{col 82}{space 3}0.934{col 90}{space 4} -.962007{col 103}{space 3} 1.046222
{txt}{hline 49}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891094{col 50}    25{col 58}  3782238{col 69}  3782557
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0509063{col 26}{space 2} .0341925{col 37}{space 1}    1.49{col 46}{space 3}0.140{col 54}{space 4}-.0168988{col 67}{space 3} .1187113
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0152207{col 26}{space 2} .0167619{col 37}{space 1}    0.91{col 46}{space 3}0.366{col 54}{space 4}-.0180187{col 67}{space 3} .0484602
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0524324{col 26}{space 2} .0216625{col 37}{space 1}    2.42{col 46}{space 3}0.017{col 54}{space 4} .0094749{col 67}{space 3} .0953899
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub - 1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0372117{col 26}{space 2} .0172696{col 37}{space 1}    2.15{col 46}{space 3}0.033{col 54}{space 4} .0029654{col 67}{space 3}  .071458
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub+ 1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0614059{col 26}{space 2} .0409318{col 37}{space 1}    1.50{col 46}{space 3}0.137{col 54}{space 4}-.0197634{col 67}{space 3} .1425752
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub + 1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0664212{col 26}{space 2} .0202394{col 37}{space 1}    3.28{col 46}{space 3}0.001{col 54}{space 4} .0262857{col 67}{space 3} .1065567
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0665381{col 26}{space 2} .0231494{col 37}{space 1}    2.87{col 46}{space 3}0.005{col 54}{space 4}  .020632{col 67}{space 3} .1124443
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub - 1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0001169{col 26}{space 2} .0281029{col 37}{space 1}    0.00{col 46}{space 3}0.997{col 54}{space 4}-.0556121{col 67}{space 3} .0558459
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES [MINORITY MEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority_het#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0512005{col 26}{space 2} .0191157{col 37}{space 1}    2.68{col 46}{space 3}0.009{col 54}{space 4} .0132933{col 67}{space 3} .0891076
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (2.minority_het#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0141057{col 26}{space 2} .0297025{col 37}{space 1}    0.47{col 46}{space 3}0.636{col 54}{space 4}-.0447955{col 67}{space 3} .0730069
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. save "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\2010-2019_DATA FINAL.08-07-2024.post-estimation.dta", replace 
{txt}{p 0 4 2}
(file {bf}
C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\2010-2019_DATA FINAL.08-07-2024.post-estimation.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\2010-2019_DATA FINAL.08-07-2024.post-estimation.dta{rm}
saved
{p_end}

{com}. 
. 
. ************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. ************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. clear
{txt}
{com}. 
. *** FIGURE 1: PLOT ELASTICITY COEFFICIENTS FOR MODELS 1-2 USING LINCOMS ABOVE FOR EACH MODEL [4 VERTICAL PLOTS]:  ///
> 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figure1.xlsx", sheet("Sheet1") firstrow
{res}{text}(5 vars, 8 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(circle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE 1" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(By Respondent Single Social Identity Group)", size(medsmall)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("AD Estimates [Differentials by Respondent Single Social Identity Group]" "(Models 1&2)", size(small)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5) 
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE 2: PLOT ELASTICITY COEFFICIENTS FOR MODELS 3-4 USING LINCOMS ABOVE FOR EACH MODEL [8 VERTICAL PLOTS]:  ///
> 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figure2.xlsx", sheet("Sheet1") firstrow
{res}{text}(10 vars, 12 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange)) (scatter estimates row if group ==3, symbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==4, symbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==5, symbol(square) mcolor(navy))(scatter estimates row if group ==6, symbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==7, symbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==8, symbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 6 "Race/Ethnicity") pos(6)) title("FIGURE 2"  "Relationship Between Authority Differentials and D&I Employee Evaluations" `"(By Respondent Intersectional Social Identity Group)"', size(medsmall)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("Gender AD Effects: by Respondent Intersectionality Group   Race/Ethnicity AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE 3: PLOT ELASTICITY COEFFICIENTS FOR MODELS 5-8 USING LINCOMS ABOVE FOR EACH MODEL [12 VERTICAL PLOTS]: NON-SUPERVISOR RESPONDENT ESTIMATES: ///
> 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figure3.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently  
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) xlabel("", noticks) title("FIGURE 3" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(Non-Supervisory Respondents: Single and Intersectional Social Identity Groups)", size(medsmall)) ylabel(-0.1(.1)0.2, labsize (small) angle(horizon)) xtitle("AD Effects: by Respondent Single Identity Group     AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE 4: PLOT ELASTICITY COEFFICIENTS FOR MODELS 5-8 USING LINCOMS ABOVE FOR EACH MODEL [12 VERTICAL PLOTS]: SUPERVISOR RESPONDENT ESTIMATES: ///
> 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figure4.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) xlabel("", noticks) title("FIGURE 4" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(Supervisor Respondents: Single and Intersectional Social Identity Groups)", size(medsmall)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("AD Effects: by Respondent Single Identity Group     AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. ************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority DIfferentials.MANUSCRIPT & DESCRIPTIVE RESULTS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 7 Aug 2024, 15:13:38
{txt}{.-}
{smcl}
{txt}{sf}{ul off}